12 Machine Learning (ML) Jobs in Coimbatore | Machine Learning (ML) Job openings in Coimbatore

TECHJAYS

THE AI REIMAGINATION COMPANY

AI Quality Engineer

Position : AI Quality Engineer

Experience : 3–10 Years

Location : Coimbatore / Hybrid

Joining : Immediate / Within 30 Days

Primary SkillsManual & Functional Testing, AI/ML Application Testing, LLM Testing, Prompt Testing, Test Case Design, API Testing, Regression Testing, Defect Management

Preferred SkillsRAG Testing, Chatbot Testing, AI Response Evaluation, Selenium, Playwright, Cypress, Python, JavaScript, SQL, Postman, JIRA, BDD

About Techjays

At Techjays, we're helping businesses reimagine how they build, operate, and scale with AI at the core. We focus on developing intelligent, scalable, and production-grade AI solutions that solve real-world business challenges.

Our global team brings together experienced technology professionals from organizations such as Google, NetApp, ADP, Cognizant Consulting, and Capgemini. We work with global clients to build AI-powered applications, intelligent automation platforms, and enterprise software solutions.

We're looking for an AI Quality Engineer with strong functional testing expertise and prior hands-on experience testing AI/ML-powered applications.

This role goes beyond traditional software testing. You will be responsible for validating the quality, accuracy, reliability, and behaviour of AI-powered features, ensuring that intelligent applications perform consistently across different scenarios and real-world use cases.

The ideal candidate should understand both traditional QA methodologies and the unique testing challenges associated with AI systems, including non-deterministic outputs, prompt behaviour, hallucinations, response relevance, and edge-case validation.

Prior hands-on experience testing AI/ML-based products or applications is mandatory. Candidates with only traditional manual testing experience and no AI project exposure will not be a fit.

Key Responsibilities

1. AI Application & LLM Testing

• Perform functional and quality testing of AI-powered applications, LLM-based products, chatbots, and intelligent automation systems.
• Design test scenarios to validate AI-generated responses for accuracy, relevance, consistency, completeness, and contextual understanding.
• Test prompts, prompt variations, and conversational flows to identify unexpected outputs and behavioural inconsistencies.
• Evaluate AI responses for hallucinations, incorrect information, irrelevant answers, and context retention issues.
• Validate AI application behaviour across different user inputs, edge cases, and complex scenarios.
• Test RAG-based applications by validating document retrieval, response relevance, contextual accuracy, and source grounding.
• Evaluate AI-powered search, recommendation engines, and other intelligent product features.
• Collaborate with AI engineers and data science teams to define acceptance criteria and quality benchmarks.

2. Functional & Manual Testing

• Analyse business and technical requirements and convert them into comprehensive test scenarios and test cases.
• Execute functional, regression, integration, system, and user acceptance testing across web and mobile applications.
• Validate end-to-end application workflows, business logic, user interactions, and data processing.
• Identify functional gaps, unexpected behaviour, and usability issues.
• Perform exploratory testing to uncover defects that may not be covered by predefined test cases.
• Ensure application functionality remains stable across different releases and environments.
• Review requirements early in the development lifecycle to identify potential quality risks.

3. AI Quality Evaluation & Validation

• Develop structured testing approaches for non-deterministic AI outputs using behaviour-based, range-based, and scenario-based validation.
• Evaluate AI response quality against expected outcomes and predefined acceptance criteria.
• Validate prompt sensitivity, context handling, conversation memory, and multi-turn interactions.
• Identify failure patterns involving hallucinations, prompt injection, incorrect retrieval, and inconsistent responses.
• Test AI system performance across different input formats, languages, and user scenarios where applicable.
• Maintain test datasets and evaluation scenarios for repeatable AI quality assessment.
• Work with engineering teams to identify root causes of AI-related defects and verify fixes.

4. API & Integration Testing

• Perform manual API testing using Postman or similar tools.
• Validate API request and response structures, status codes, authentication, authorization, and error handling.
• Test integrations between AI services, backend systems, databases, and external APIs.
• Validate data flow between application components and identify integration issues.
• Test API behaviour under different input conditions, including invalid inputs and boundary cases.
• Verify API responses and ensure consistency between frontend and backend functionality.

5. Defect Management & Quality Reporting

• Identify, document, track, and manage defects throughout the testing lifecycle.
• Maintain detailed test cases, test execution reports, defect logs, and test documentation.
• Collaborate with developers to reproduce issues, analyse root causes, and validate fixes.
• Track test coverage, defect trends, and application quality metrics.
• Communicate release risks, unresolved defects, and testing status to relevant stakeholders.
• Participate in release readiness reviews and provide quality sign-off for assigned modules.

6. Automation & Continuous Improvement

• Identify repetitive test scenarios that can be automated to improve testing efficiency.
• Support automation initiatives using Selenium, Playwright, or Cypress.
• Work with developers to improve testability and integrate testing practices into CI/CD workflows.
• Explore AI-assisted testing tools and approaches to improve test coverage and efficiency.
• Continuously improve testing methodologies for both conventional software applications and AI-powered systems.

Required Skills & Experience

1. Functional & Manual QA

• 3–5 years of hands-on experience in manual and functional software testing.
• Strong understanding of software testing methodologies, SDLC, STLC, and defect management.
• Experience designing and executing test cases for functional, regression, integration, and end-to-end testing.
• Strong knowledge of Agile/Scrum methodologies and sprint-based QA processes.
• Experience testing web applications, APIs, and mobile applications.
• Ability to analyse requirements and identify functional gaps, edge cases, and potential risks.

2. Mandatory AI/ML Testing Experience

• Prior hands-on experience testing AI/ML-powered applications or products.
• Practical experience testing LLM-based applications, AI chatbots, conversational systems, or intelligent automation features.
• Understanding of prompt testing and evaluating AI-generated responses.
• Ability to validate AI outputs for accuracy, relevance, consistency, and contextual correctness.
• Experience identifying hallucinations, unexpected AI behaviour, and response-quality issues.
• Understanding of AI application workflows, model outputs, and the challenges associated with non-deterministic systems.
• Experience collaborating with AI/ML engineers or data science teams during testing and validation.

3. API & Integration Testing

• Hands-on experience with manual API testing using Postman.
• Understanding of REST APIs, JSON, request/response validation, authentication, and error handling.
• Experience validating integrations between frontend, backend, and external services.
• Basic understanding of database validation and SQL queries.

4. Testing Tools & Technologies

• Experience with JIRA and Confluence for defect tracking and test documentation.
• Familiarity with Postman, SQL, and browser developer tools.
• Understanding of test management and reporting practices.
• Basic knowledge of BDD frameworks such as Cucumber/Gherkin is an advantage.

Preferred Skills

• Experience testing RAG-based applications, including document retrieval and contextual response validation.
• Exposure to vector databases and semantic search testing.
• Familiarity with LangChain, LangGraph, LlamaIndex, or similar AI frameworks.
• Understanding of LLM evaluation frameworks and AI quality assessment methodologies.
• Experience with AI evaluation tools such as Ragas, DeepEval, or similar frameworks.
• Exposure to prompt injection, adversarial testing, and responsible AI validation.
• Working knowledge of Selenium, Playwright, or Cypress.
• Basic scripting knowledge in Python or JavaScript.
• Familiarity with CI/CD pipelines and automated testing practices.
• Exposure to cross-browser testing tools such as BrowserStack or Sauce Labs.

What We're Looking For Beyond Skills

• AI Testing Mindset: Understands that testing AI applications requires more than checking whether a feature works. Can evaluate response quality, accuracy, relevance, and behaviour.
• Analytical Thinking: Ability to identify unusual scenarios, inconsistent outputs, and hidden quality issues.
• Strong QA Fundamentals: Applies structured testing methodologies while adapting them to AI-powered applications.
• Attention to Detail: Documents defects clearly and identifies patterns in application and AI behaviour.
• Ownership: Takes responsibility for testing quality from requirement analysis through release validation.
• Collaboration: Works effectively with developers, AI engineers, product managers, and data science teams.
• Continuous Learning: Interested in exploring emerging AI technologies and evolving testing methodologies.
• Communication: Clearly communicates test results, defect impact, quality risks, and release readiness.

What We Offer

• Competitive compensation aligned with experience and expertise.
• Flexible work environment (Coimbatore office / Hybrid).
• Paid holidays and flexible time off.
• Medical insurance covering self and family, up to ₹4 lakh per person.
• Opportunity to work on real-world AI-powered products and enterprise applications.
• Hands-on exposure to LLMs, RAG systems, agentic AI, and modern AI engineering practices.
• Opportunities to develop expertise in AI quality engineering and automation testing.
• A collaborative, multicultural environment with opportunities for professional growth.
• A culture that values clarity, integrity, ownership, and continuous learning.

Join Techjays

If you're passionate about software quality and have hands-on experience validating AI-powered applications, we'd love to hear from you.

Join us in building reliable, intelligent, and production-ready AI systems.

Data Science (SME)

FACE Prep is India’s leading employability and industry-aligned education company. For over 17 years, we have partnered with higher education institutions to bridge the gap between academia and industry.

● Worked with 2,000+ colleges and universities across India

● Trained 6+ million students across disciplines

● Market leaders in:

● Employability skills & placement readiness

● Industry-aligned academic papers(credit-bearing)

● Full-scale industry-aligned degree programs with universities

● Pan-India operations, headquartered in Coimbatore

● Young, energetic, mission-driven team

● Fast-growing organization with headcount expected to cross 1,000 employees in the next financial year

At FACE Prep, people are the platform on which outcomes are built.

Position: Data Science (SME)

Location: Coimbatore

Duration: Full-Time

Department: Training & Development

Experience: Minimum 2 Years

Role Description :

The Data Science Subject Matter Expert (SME) is a full-time, on-site role based in Coimbatore. The SME will design and deliver data science curricula, including lectures, hands-on labs, and project-based learning for students preparing for tech careers. Daily responsibilities include creating educational content, developing problem sets and case studies, mentoring learners on data analysis and model-building, and reviewing student work to provide constructive feedback. The SME will collaborate with other trainers and the product team to align content with current industry practices and hiring requirements. The role also involves analyzing learner performance data, refining teaching strategies, and occasionally contributing to workshops, bootcamps, and online learning materials.

Requirements:

• Strong foundation in Statistics and Data Science, with the ability to explain complex concepts clearly and practically.

• Hands-on experience in Data Analytics and Data Analysis, including working with real-world datasets and deriving actionable insights.

• Excellent Analytical Skills for problem-solving, designing assignments, and guiding learners through data-driven decision-making.

• Proficiency in common data science tools and languages (e.g., Python/R, SQL, data visualization tools such as Tableau/Power BI).

• Prior experience in teaching, mentoring, corporate training, or curriculum development is highly beneficial.

• Bachelor’s or Master’s degree in a quantitative field such as Computer Science, Statistics, Mathematics, Data Science, or related discipline.

• Ability to communicate effectively with diverse learner groups and collaborate within a multidisciplinary team.

• Exposure to machine learning concepts, model evaluation, and deployment practices is a plus.

IMMEDIATE JOINERS REQUIRED

Python Machine Learning Engineer / Data Scientist (GCP)

Experience: Typically 6–10 Years (based on JD complexity)

Primary Skills: Python, Machine Learning, Data Analysis, Google Cloud Platform (GCP)

Must-Have Skills (ON)

• Python
• Machine Learning
• Data Analysis
• Exploratory Data Analysis (EDA)
• Google Cloud Platform (GCP)
• BigQuery
• Vertex AI
• Cloud Storage
• Cloud Functions
• Pandas
• NumPy
• Scikit-Learn
• TensorFlow OR PyTorch
• Statistical Analysis
• Predictive Modeling
• Business Stakeholder Management
• Requirement Gathering
• Root Cause Analysis
• Data-Driven Decision Making

Your Responsibilities

what you will wake up to solve.

• Process-First AI Strategy: Principal Technical Expert: Act as a hands-on leader and the core technical authority tasked with "futurifying" client businesses through advanced AI. Take full ownership of the AI Engineering squad, transforming ambitious concepts into high-impact, tangible realities.
• Engineering & Intelligent Deployment: Execute the full-lifecycle development of innovative AI/ML solutions, including hands-on design, coding, testing, and deployment of robust, scalable systems that prioritize technical excellence and business relevance.
• Scalability & Architectural Optimization: Directly build and optimize high-performance AI architectures and core system components to ensure solutions are reliable, production-ready, and optimized for long-term operational success.
• Impact-Driven Technical Expertise: Deliver intelligent client outcomes through direct technical contribution, maintaining an "Always Beta" mindset and a relentless focus on solving complex engineering challenges.
• Leadership through Action: Lead by example rather than control, coaching and mentoring a high-performing squad of "happier Do-ers" to foster a vibrant culture of continuous innovation and technical excellence.
• Strategic Integration & Collaboration: Partner across internal teams to translate chaotic business challenges into precise technical requirements, ensuring seamless solution integration and adoption for global clients.
• The "Agentic" Shift: You will lead the transition from simple predictive models to Agentic Workflows. You will build systems where AI agents can plan, reason, and execute complex tasks autonomously to solve intricate business problems.
• Talent & Culture: You will mentor a high-performance squad of AI Engineers and Data Scientists. You will teach them to look beyond the algorithm and understand the business outcome.

Functional Skills

Scaling Intelligent Workforce through Delivery Excellence

• Deep Technical Acumen: Operates at the cutting edge of AI, applying advanced technical knowledge to engineer and implement groundbreaking solutions, and guide the squad in developing future capabilities.
• Client Advocacy & Revenue Growth: Skill in cultivating and maintaining trusted client partnerships. Drives strategic engagement that results in repeat business and expanded client portfolios within the region.
• Contract & Risk Governance: High proficiency in reviewing and managing complex project agreements (SoW), mitigating delivery risks, and navigating commercial negotiations to safeguard BU profitability.
• Structured Problem-Solving: Simplifies chaotic technical challenges for the squad by breaking them into solvable chunks using first-principles thinking.
• Squad Delivery Ownership: Follows through on the squad's solution execution—owning technical outcomes from ideation to deployment with rigor, precision, and pride, ensuring tangible, real-world business value.

Technical Oversight & Execution Charter

• Technical Troubleshooting & Crisis Resolution: Actively manages technical roadblocks within the squad, personally intervening to troubleshoot ML or MLOps constraints. You ensure the protection of sprint timelines and the guaranteed performance of deployed models through hands-on problem-solving.
• Cloud-Native Technical Command: Maintains deep, functional knowledge of modern AI system design (e.g., RAG Frameworks, Agentic Workflows, and Inference Optimization) across GCP and AWS. You hold the responsibility to validate squad-level technical roadmaps, ensuring they are technically feasible and production-hardened.
• End-to-End Project Management: Expertly manage all aspects of a project, including scope, budget, timelines, and stakeholder communication. Accountable for the entire delivery, not just the technical parts.
• Talent Strategy & Mentorship: Drive the hiring and development of specialized talent. You will be responsible for defining and optimizing effective team structures while proactively fostering an environment that champions creative problem-solving and technical agility.

Tech Superpowers

• Deep AI Engineering Mastery & Guidance: Possesses profound, hands-on expertise in engineering, optimizing, and deploying foundational models, custom AI solutions, and complex multi-modal systems. You'll also guide your squad in understanding model architectures, training methodologies, and ethical AI development from the ground up, ensuring their collective proficiency.
• Intelligent Systems Architecture & Oversight: You'll directly contribute to and oversee the coding and implementation of robust, scalable, and production-grade AI platforms and MLOps components for your squad's projects. You'll translate abstract technical requirements into high-performance, maintainable AI system designs, always considering reliability, security, and future extensibility across the squad's work.
• Cloud-Native AI capability: More than cloud-certified, you are deeply cloud-capable in applied AI engineering. You proficiently leverage and guide your team in utilizing leading cloud AI/ML ecosystems to build, deploy, and manage AI solutions.
• Technical Integrity & Ethical Governance: Establishes and audits mandatory technical quality benchmarks, ensuring strict adherence to rigorous policies regarding model validation, automated testing coverage, and ethical governance.

Experience & Relevance

• A value-driven AI/ML Engineering Manager with 8+ years of experience in building and scaling end-to-end AI engineering and solution delivery.
• Leadership Track Record: Proven track record as a hands-on builder, and lead, contributing to the design, development, and deployment of complex, enterprise-grade AI/ML platforms and solutions. Expert in leveraging Google Cloud's AI/ML ecosystem (Vertex AI, BigQuery ML, GKE for MLOps) to deliver highly performant, scalable, and impactful AI transformations.
• Delivery & Advisory Record: Experience in building and optimizing intelligent systems and personally driving the technical execution from conception to scalable deployment.
• Applied AI & Domain Expertise: Hands-On AI Deployment: Extensive hands-on experience deploying AI-powered workflows, copilots, and automation solutions in production environments.
• Client-Facing Lead: Demonstrated hands-on experience as an AI/ML Product Manager, Data Science Manager, or Technical Architect in client-facing capacities. This involves directly building, implementing, and advising on complex AI solutions, consistently acting as the trusted technical authority for strategic clients.

Bonus Points (you will thrive if you have)

• Founder’s Energy: Bias for action, thrive in ambiguity, relentless focus on outcomes.
• Low-Code/No-Code Fluency: Experience with AI integrations via Power Platform or similar.
• AI Copilots & Extensions: Built plugins, copilots, or agentic automation frameworks.
• Thought Leadership DNA: Industry content creation, technical blogs, public speaking.
• Ethical Compass: Strong commitment to responsible AI practices.
• Engineer at Heart: Background in product development or engineering before moving into architecture.

Your Responsibilities

what you will wake up to solve.

• Process-First AI Strategy: Principal Technical Expert: Act as a hands-on leader and the core technical authority tasked with "futurifying" client businesses through advanced AI. Take full ownership of the AI Engineering squad, transforming ambitious concepts into high-impact, tangible realities.
• Engineering & Intelligent Deployment: Execute the full-lifecycle development of innovative AI/ML solutions, including hands-on design, coding, testing, and deployment of robust, scalable systems that prioritize technical excellence and business relevance.
• Scalability & Architectural Optimization: Directly build and optimize high-performance AI architectures and core system components to ensure solutions are reliable, production-ready, and optimized for long-term operational success.
• Impact-Driven Technical Expertise: Deliver intelligent client outcomes through direct technical contribution, maintaining an "Always Beta" mindset and a relentless focus on solving complex engineering challenges.
• Leadership through Action: Lead by example rather than control, coaching and mentoring a high-performing squad of "happier Do-ers" to foster a vibrant culture of continuous innovation and technical excellence.
• Strategic Integration & Collaboration: Partner across internal teams to translate chaotic business challenges into precise technical requirements, ensuring seamless solution integration and adoption for global clients.
• The "Agentic" Shift: You will lead the transition from simple predictive models to Agentic Workflows. You will build systems where AI agents can plan, reason, and execute complex tasks autonomously to solve intricate business problems.
• Talent & Culture: You will mentor a high-performance squad of AI Engineers and Data Scientists. You will teach them to look beyond the algorithm and understand the business outcome.

Functional Skills

1. Scaling Intelligent Workforce through Delivery Excellence

• Deep Technical Acumen: Operates at the cutting edge of AI, applying advanced technical knowledge to engineer and implement groundbreaking solutions, and guide the squad in developing future capabilities.
• Client Advocacy & Revenue Growth: Skill in cultivating and maintaining trusted client partnerships. Drives strategic engagement that results in repeat business and expanded client portfolios within the region.
• Contract & Risk Governance: High proficiency in reviewing and managing complex project agreements (SoW), mitigating delivery risks, and navigating commercial negotiations to safeguard BU profitability.
• Structured Problem-Solving: Simplifies chaotic technical challenges for the squad by breaking them into solvable chunks using first-principles thinking.
• Squad Delivery Ownership: Follows through on the squad's solution execution—owning technical outcomes from ideation to deployment with rigor, precision, and pride, ensuring tangible, real-world business value.

2. Technical Oversight & Execution Charter

• Technical Troubleshooting & Crisis Resolution: Actively manages technical roadblocks within the squad, personally intervening to troubleshoot ML or MLOps constraints. You ensure the protection of sprint timelines and the guaranteed performance of deployed models through hands-on problem-solving.
• Cloud-Native Technical Command: Maintains deep, functional knowledge of modern AI system design (e.g., RAG Frameworks, Agentic Workflows, and Inference Optimization) across GCP and AWS. You hold the responsibility to validate squad-level technical roadmaps, ensuring they are technically feasible and production-hardened.
• End-to-End Project Management: Expertly manage all aspects of a project, including scope, budget, timelines, and stakeholder communication. Accountable for the entire delivery, not just the technical parts.
• Talent Strategy & Mentorship: Drive the hiring and development of specialized talent. You will be responsible for defining and optimizing effective team structures while proactively fostering an environment that champions creative problem-solving and technical agility.

Tech Superpowers

• Deep AI Engineering Mastery & Guidance: Possesses profound, hands-on expertise in engineering, optimizing, and deploying foundational models, custom AI solutions, and complex multi-modal systems. You'll also guide your squad in understanding model architectures, training methodologies, and ethical AI development from the ground up, ensuring their collective proficiency.
• Intelligent Systems Architecture & Oversight: You'll directly contribute to and oversee the coding and implementation of robust, scalable, and production-grade AI platforms and MLOps components for your squad's projects. You'll translate abstract technical requirements into high-performance, maintainable AI system designs, always considering reliability, security, and future extensibility across the squad's work.
• Cloud-Native AI capability: More than cloud-certified, you are deeply cloud-capable in applied AI engineering. You proficiently leverage and guide your team in utilizing leading cloud AI/ML ecosystems to build, deploy, and manage AI solutions.
• Technical Integrity & Ethical Governance: Establishes and audits mandatory technical quality benchmarks, ensuring strict adherence to rigorous policies regarding model validation, automated testing coverage, and ethical governance.

Experience & Relevance

• A value-driven AI/ML Engineering Manager with 8+ years of experience in building and scaling end-to-end AI engineering and solution delivery.
• Leadership Track Record: Proven track record as a hands-on builder, and lead, contributing to the design, development, and deployment of complex, enterprise-grade AI/ML platforms and solutions. Expert in leveraging Google Cloud's AI/ML ecosystem (Vertex AI, BigQuery ML, GKE for MLOps) to deliver highly performant, scalable, and impactful AI transformations.
• Delivery & Advisory Record: Experience in building and optimizing intelligent systems and personally driving the technical execution from conception to scalable deployment.
• Applied AI & Domain Expertise: Hands-On AI Deployment: Extensive hands-on experience deploying AI-powered workflows, copilots, and automation solutions in production environments.
• Client-Facing Lead: Demonstrated hands-on experience as an AI/ML Product Manager, Data Science Manager, or Technical Architect in client-facing capacities. This involves directly building, implementing, and advising on complex AI solutions, consistently acting as the trusted technical authority for strategic clients.

Bonus Points (you will thrive if you have)

• Founder’s Energy: Bias for action, thrive in ambiguity, relentless focus on outcomes.
• Low-Code/No-Code Fluency: Experience with AI integrations via Power Platform or similar.
• AI Copilots & Extensions: Built plugins, copilots, or agentic automation frameworks.
• Thought Leadership DNA: Industry content creation, technical blogs, public speaking.
• Ethical Compass: Strong commitment to responsible AI practices.
• Engineer at Heart: Background in product development or engineering before moving into architecture.

Why you’ll love being a ‘Searcian’

NOT your ‘usual’ management consultancy; we ‘solve differently’.

• We are happier. No really happier’: A vibrant, inclusive, and supportive work environment. We even have a dedicated role for ‘Better Living’.
• The Company You Keep (Says Everything): solvers. engineers. tinkerers. improvers. futurists operating across 12 countries.
• No room for CAVEers (Constantly Against Virtually Everything people). Instead, we make room for a meditation room in our offices.
• No bloat: 27 people meeting with 23 clueless people. Not happening here. We also don't do the meetings to plan for pre-meetings.
• No bureaucracy. Zero entropy. Real decision-making velocity: We’re large enough to solve the world’s most complex business challenges, yet small and agile enough to value individual humans. With us, you’re a name, not an employee ID number lost in a sea of 37,000 people where it takes a year just to decide ‘who will decide’.
• Ideas over Hierarchy: We reject HiPPOs (Highest Paid Person’s Opinion). The most well-reasoned ideas win - regardless of whose name is on them. That dangerous phrase, "We’ve always done it this way," dies here.
• Own-the-outcome: The buck stops with you. Doesn’t matter if you are an intern. (Psst: A ‘real intern’ actually drafted this JD.)
• Expert ‘wholesome generalists’, Not ‘one-nut-tighteners’. At Searce, you see the whole picture — how the car is designed, built, and driven — not just how to tighten the third nut on a red 1962 Ford Falcon owned by Vinny’s cousin. Real impact comes from knowing why that nut matters to the person behind the wheel.
• You ‘do stuff’ that matters. Not just “follow up on the deck we shared.”
• Gain more years in your Searce-perience: We operate at a 3.65x experience velocity—yes, we measured it. (and charted it to the scale too)

Join the ‘real solvers’

ready to futurify?

If you are excited by the possibilities of what an AI-native engineering-led, modern tech consultancy can do to futurify businesses, apply here and experience the ‘Art of the possible’. Don’t Just Send a Resume. Send a Statement.

Job Title: Deployment Lead (Python, Linux, AWS) 

Location: Coimbatore

Overview 

We are seeking an experienced Deployment Lead to oversee the end-to-end deployment lifecycle of our applications and services. The ideal candidate will have deep expertise in Python, strong Linux administration skills, and hands-on experience with AWS cloud infrastructure. You will work closely with engineering, DevOps, QA, and product teams to ensure reliable, repeatable, and scalable deployments across multiple environments. 

Key Responsibilities 

• Lead and manage deployment activities for all application releases across development, staging, and production environments. 
• Develop and maintain deployment automation, scripts, and tools using Python and shell scripting. 
• Own and optimize CI/CD pipelines (e.g., GitHub Actions, Jenkins, GitLab CI, or AWS CodePipeline). 
• Oversee Linux server administration, including configuration, troubleshooting, performance optimization, and security hardening. 
• Design, implement, and maintain AWS infrastructure (EC2, S3, Lambda, IAM, RDS, ECS/EKS, CloudFormation/Terraform). 
• Ensure robust monitoring, logging, and alerting using tools such as CloudWatch, Grafana, Prometheus, or ELK. 
• Collaborate with developers to improve code readiness for deployment and production reliability. 
• Manage environment configurations and ensure consistency and version control across environments. 
• Lead incident response during production issues; conduct root-cause analysis and implement long-term fixes. 
• Establish and enforce best practices for deployment, configuration management, and operational excellence. 

Required Skills & Qualifications 

• 5+ years of experience in deployment engineering, DevOps, or site reliability engineering roles. 
• Strong proficiency in Python for automation and tooling. 
• Advanced experience with Linux systems administration (Ubuntu, CentOS, Amazon Linux). 
• Hands-on work with AWS cloud services and infrastructure-as-code (CloudFormation or Terraform). 
• Experience with containerization technologies such as Docker and orchestration platforms like ECS, EKS, or Kubernetes. 
• Strong understanding of CI/CD tools and automated deployment strategies. 
• Familiarity with networking concepts: DNS, load balancers, VPCs, firewalls, VPN, and routing. 
• Expertise with monitoring, alerting, and logging solutions. 
• Strong problem-solving and analytical skills; able to lead troubleshooting efforts. 
• Excellent communication and leadership abilities. 

Position: Assistant Professor

Department: CSE / IT

Experience: 0 – 15 Years

Joining: Immediate / Within 1 Month

Salary: As per norms and experience

🎓 Qualification:

ME / M.Tech in Computer Science Engineering / Information Technology

Ph.D. (Preferred but not mandatory)

First Class in UG & PG as per AICTE norms

🔍 Roles & Responsibilities:

Deliver high-quality lectures for UG / PG programs

Prepare lesson plans, course materials, and academic content

Guide student projects and internships

Participate in curriculum development and academic planning

Conduct internal assessments, evaluations, and result analysis

Mentor students for academic and career growth

Participate in departmental research activities

Publish research papers in reputed journals (Scopus/SCI preferred)

Attend Faculty Development Programs (FDPs), workshops, and conferences

Contribute to NAAC / NBA accreditation processes

Support institutional administrative responsibilities

💡 Required Skills:

Strong subject knowledge in CSE / IT domains

Programming proficiency (Python, Java, C++, Data Structures, AI/ML, Cloud, etc.)

Excellent communication and presentation skills

Research orientation and academic enthusiasm

Team collaboration and mentoring ability

Role: Senior AI Engineer

Work Location: TechGenzi Coimbatore Office (ODC for Tiramai.ai)

Employment Type: Full-time

Experience: 2–5 years (Full-stack development with AI exposure)

About the Role & Work Location.

The selected candidate will be employed by Tiramai.ai and will work exclusively on Tiramai.ai projects. The role will be based out of TechGenzi’s Coimbatore office, which functions as an Offshore Development Center (ODC) supporting Tiramai.ai’s product and engineering initiatives.

Primary Focus

As an AI Engineer at our enterprise SaaS and AI-native organization, you will play a pivotal role in building secure, scalable, and intelligent digital solutions. This role combines full-stack development expertise with applied AI skills to create next-generation platforms that empower enterprises to modernize and act smarter with AI. You will work on AI-driven features, APIs, and cloud-native applications that are production-ready, compliance-conscious, and aligned with our mission of delivering responsible AI innovation.

Key Responsibilities

• Design, develop, and maintain full-stack applications using Python (backend) and React/Angular (frontend).
• Build and integrate AI-driven modules, leveraging GenAI, ML models, and AI-native tools into enterprise-grade SaaS products.
• Develop scalable REST APIs and microservices with security, compliance, and performance in mind.
• Collaborate with architects, product managers, and cross-functional teams to translate requirements into production-ready features.
• Ensure adherence to secure coding standards, data privacy regulations, and human-in-the-loop AI principles.
• Participate in code reviews, system design discussions, and continuous integration/continuous deployment (CI/CD) practices.
• Contribute to reusable libraries, frameworks, and best practices to accelerate AI platform development.

Skills Required

• Strong proficiency in Python for backend development.
• Frontend expertise in React.js or Angular with 2+ years of experience.
• Hands-on experience in full SDLC development (design, build, test, deploy, maintain).
• Familiarity with AI/ML frameworks (e.g., TensorFlow, PyTorch) or GenAI tools (LangChain, vector DBs, OpenAI APIs).
• Knowledge of cloud-native development (AWS/Azure/GCP), Docker, Kubernetes, and CI/CD pipelines.
• Strong understanding of REST APIs, microservices, and enterprise-grade security standards.
• Ability to work collaboratively in fast-paced, cross-functional teams with strong problem-solving and analytical skills.
• Exposure to responsible AI principles (explainability, bias mitigation, compliance) is a plus.

Growth Path

• AI Engineer (24 years) focus on full-stack + AI integration, delivering production-ready features.
• Senior AI Engineer (4–6 years) lead modules, mentor juniors, and drive AI feature development at scale.
• Lead AI Engineer (6–8 years) own solution architecture for AI features, ensure security/compliance, collaborate closely with product/tech leaders.
• AI Architect / Engineering Manager (8+ years) shape AI platform strategy, guide large-scale deployments, and influence product/technology roadmap.

Job Title: Data Science Trainer

Location: Coimbatore

Employment Type: Full-time

Job Summary:

We are seeking an experienced and passionate Data Science Trainer to deliver engaging and practical training sessions to students or professionals. The trainer will design curriculum, prepare materials, and guide learners in developing data science skills through real-world projects and case studies.

Key Responsibilities:

• Develop and deliver comprehensive training programs on Data Science concepts, tools, and techniques.
• Teach topics including but not limited to:
• Data Analysis (NumPy, Pandas, Data Cleaning, EDA)
• Data Visualization (Matplotlib, Seaborn, Plotly)
• Statistics & Probability (Descriptive, Inferential)
• Machine Learning (Supervised & Unsupervised Algorithms, Model Evaluation)
• Deep Learning (Neural Networks, TensorFlow, PyTorch – if applicable)
• Big Data Tools (Hadoop, Spark – if applicable)
• Provide hands-on training with industry-relevant datasets and projects.
• Prepare lesson plans, assignments, assessments, and evaluation reports.
• Mentor learners individually to ensure conceptual clarity and practical application.
• Keep training content updated with the latest industry trends and technologies.
• Collaborate with the academic or corporate training team for curriculum improvement.

Required Skills & Qualifications:

• Bachelor’s/Master’s degree in Computer Science, Statistics, Mathematics, or related field.
• Proven experience in Data Science, Machine Learning, and Data Analytics.
• Proficiency in Python (NumPy, Pandas, Scikit-learn, etc.) and SQL.
• Strong understanding of statistical concepts and their application in data analysis.
• Experience with visualization tools like Tableau/Power BI is a plus.
• Excellent communication and presentation skills.
• Ability to simplify complex concepts for learners with varied backgrounds.
• Prior teaching/training experience preferred.

·        Qualification: bachelor’s or master’s degree in computer science, Engineering, or related field.

·        Proven 4+ years of experience in full stack development, including proficiency with React, Tailwind CSS, Python, and Flask.

·        Strong understanding of Graph QL concepts and hands-on experience with Ariadne or similar frameworks.

·        Familiarity with containerization using Docker for application deployment.

·        Demonstrated expertise in machine learning model integration, preferably using the Hugging Face framework.

·        Experience deploying machine learning models on cloud platforms such as Replicate and AWS is a strong plus.

·        Excellent problem-solving skills and a proactive attitude towards learning and adapting to new technologies.

·        Should have experience in Backend: Python, Flask Framework, Langchain ML Ops Framework, Ariadne Graph QL Framework, Docker. Frontend: React, Tailwind. ML Model Development – Hugging Face Model Training, ML Deployment onto Replicate or AWS

FURIOUS FOX is looking for Embedded Developers with strong coding skills in C & C++ as well as experience with Embedded Linux.

Experience : (Minimum 7-10 yrs)

• Experienced in edge processing for connected building / industrial / consumer

appliances / automotive ECU

• Have a good understanding of IoT platforms and architecture

• Deep experience in operating systems eg: Linux, freeRTOS / kernel development/device drivers.

/ sensor drivers

• Have experience with various low-level communication protocols, memory devices, messaging

framework etc.

• Have a deep understanding of design principles, design patterns, container preparations

• Have developed hardware, OS abstraction layers, and sensor handlers services to manage various BSP, os standards

• Have experience with Python edge packages.

• Have a good understanding about IoT databases for edge computing

• Good understanding of connectivity application protocols and connectivity SDK for Wi-Fi and BT / BLE

• Experienced in arm architecture, peripheral devices and hardware board configurations

• Able to set up debuggers, configure build environments, and compilers and optimize code and performance.

Skills / Tools:

• Expert at object-oriented programming

• Modular programming

• C / C++ / JavaScript / Python

• Eclipse framework

• Target deployment techniques

• IoT framework

• Test framework

Highlights :

• Having AI / ML knowledge in applications

• Have worked on wireless protocols

• Ethernet / Wi-Fi / Bluetooth / BLE

• Highly exploratory attitude

• willing to venture in and learn new

technologies.

• Have done passionate projects based on self-interest.