Prentis

Product Engineer — Role Summary

We are looking for a Product Engineer to build user-facing products that combine AI capabilities with practical applications. You will work at the intersection of software engineering and AI, developing autonomous, agent-driven systems that solve complex educational and research problems.

Key Responsibilities:

• Product Development: Design, build, and deploy production-ready applications powered by LLMs and AI agents.
• Data Engineering: Build scalable ETL/ELT pipelines to process structured and unstructured data, including text and audio, for RAG and model fine-tuning.
• Agentic Workflows: Develop multi-step AI agents with tool calling, APIs, databases, search, reasoning, and memory.
• Rapid Prototyping: Turn ideas and research concepts into interactive, production-ready applications.
• AI Integration: Use frameworks such as LangChain, LlamaIndex, AutoGen, or custom orchestrators to integrate AI into scalable systems.
• User Experience: Transform raw AI outputs into reliable, intuitive, and responsive user experiences.
• Collaboration: Work closely with ML researchers and data engineers to integrate custom and fine-tuned models.
• Observability: Monitor agent behavior, manage edge cases, reduce hallucinations, and improve reliability in production.

The ideal candidate combines strong software engineering, AI/LLM expertise, data engineering, and product thinking, with the ability to take an AI concept from prototype to production.

Full-time, permanent position implementing, supporting, and optimizing enterprise ERP systems for clients, with a focus on supply chain, manufacturing, and planning modules. The role is client-facing first: success depends as much on clear, polished communication as on functional expertise.

Required

Polished client communication: able to run status calls, present findings, and manage escalations with professionalism and composure

Ability to translate technical concepts — configurations, integrations, system behavior — into plain language for business and executive audiences

Career at an IT services company, systems integrator, ERP vendor, or consulting firm (e.g., Accenture, NTT Data, Wipro, Infosys, ERP-partner boutiques) — required; candidates whose ERP experience is exclusively in-house at a single employer will not be a fit

5–8 years in enterprise ERP (any major platform: Oracle, SAP, Workday, Dynamics, NetSuite)

At least one full-cycle implementation: requirements, configuration, testing, cutover, post-go-live support

Functional depth in SCM-adjacent modules: inventory, order management, procurement, costing, or planning

Integration exposure: REST/SOAP APIs, third-party system connections, data migration

Clear written deliverables: documentation, status reports, and issue summaries that nontechnical stakeholders can act on

Preferred

Experience presenting to steering committees or client leadership

Multi-industry client exposure

Experience automating support or testing workflows

Reporting/analytics tooling (BI, embedded ERP analytics)