

Ritually
https://ritually.aiAbout
Ritually helps enterprises identify and automate their back-office rituals. We build the process intelligence layer that shows large organizations how their highest-value, most repetitive work actually gets done and turns that work into automation, for a world where humans and agents work together.
Our founders, Ari Winkleman and Rachel Bush, previously built and exited a startup (Involvio) to Cisco. The company is funded and working with design partners.
You'll join an AI-native, repeat founding team at the earliest stage, with equity and real scope. You'll work directly with the founders, own meaningful work from 0-1 and have a real path to grow with the company.
We care deeply about trust, craft, customer obsession, and speed and that's what we look for in the people who join us!
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About Ritually
Ritually is building the definitive process discovery platform for back office work. Our product fuses underutilized system telemetry with computer vision to help large enterprise and scaling mid-market companies deeply understand and reimagine their highest value and most repetitive processes for a world where humans and agents work together. We're based in New York and Denver.
We believe deeply in trust (of our customers and each other), craft, customer obsession, and speed.
You'll be joining an AI-native, fast-moving, and repeat founding team. Ritually's founders previously built and exited a startup (Involvio) to Cisco. The company is funded and working with design partners.
The Role
This is a founding applied-AI role. You'll be building our core data pipeline and intelligence layer with the founding team from 0-1 You'll be tackling our largest technical challenges across technologies.
What You'll Do
- Design and build data pipelines that capture and turn high volumes of system activity into structured, queryable data.
- Turn raw activity streams into processes: sessionize event logs, cluster recurring sequences, and use LLMs to label and summarize what's happening.
- Build the evaluation backbone from scratch: stand up synthetic data generation pipelines that produce labeled scenarios to measure accuracy and catch regressions.
- Own data quality and privacy.
- Partner closely with the founders and the rest of engineering to ship features end to end.
What We're Looking For
- 1-4 years of experience in data engineering, AI/ML engineering, or backend work with a data focus (some of this can be project or research experience).
- Strong in Python and/or TypeScript, comfortable in SQL, and able to build data pipelines you can trust.
- Hands-on experience working with LLMs structured output, prompting, and wrangling non-determinism while keeping behavior reliable.
- A practical sense for evaluation: you know that "it looks right" isn't the same as "it's measurably right."
- Care about data privacy and handling sensitive information responsibly.
- Comfort with ambiguity and a real appetite to own a hard, open-ended problem.
Nice to Have
- Background in process mining, sequence / event-log analysis, or workflow analytics.
- Deeper PostgreSQL: window functions, partitioning, pg_cron, query performance.
- Embeddings and vector search (pgvector) or semantic retrieval.
- Familiarity with cloud infrastructure.
- Any prior early-stage startup experience.
- Degree in computer science or a related field.
About Ritually
Ritually is building the definitive process discovery platform for back office work. Our product fuses underutilized system telemetry with computer vision to help large enterprise and scaling mid-market companies deeply understand and reimagine their highest value and most repetitive processes for a world where humans and agents work together. We're based in New York and Denver.
We believe deeply in trust (of our customers and each other), craft, customer obsession, and speed.
You'll be joining an AI-native, fast-moving, and repeat founding team. Ritually's founders previously built and exited a startup (Involvio) to Cisco. The company is funded and working with design partners.
The Role
This is a founding full-stack role. You'll be building our application with the founding team from 0-1 You'll own features and infra end to end and across technologies. You'll also own how we build: ensuring our AI development workflow is fast, dependable and secure.
What You'll Do
- Build features end to end, across our desktop client, web app, and the backend services that tie them together.
- Go deep in our cross-platform Electron desktop client the native OS integration that powers on-device capture, and the on-device privacy and redaction that runs before data leaves the machine.
- Move fluidly across technologies and layers, picking up whatever a problem needs rather than staying in one corner of the stack.
- Own the infrastructure and deployment path CI/CD, releases, and the cloud services everything runs on so shipping stays routine and reliable.
- Own how we build: keep our AI development workflow fast, dependable, and secure and establish the conventions, tooling, and guardrails that let a small team build like a much larger one.
- Own observability and on-call basics logging, error tracking, and alerting so we catch issues before our customers do.
- Help set technical direction and keep the codebase legible as we scale the engineering team.
What We're Looking For
- 1-4 years building software across the stack frontend, backend, and the glue between them (internships and meaningful side projects count).
- Comfort working across multiple languages and technologies, and a genuine willingness to learn whatever a problem requires.
- Solid fundamentals in shipping production software version control, testing, debugging, and deployment.
- Experience with, or strong interest in, owning infrastructure and devops: CI/CD, cloud services, and reliability.
- Genuine excitement about AI-native development you've used AI coding agents and want to push how far they can go.
- Comfort with ambiguity and a willingness to own problems end to end in a small team.
Nice to Have
- Experience building desktop applications (Electron or native).
- Experience building internal tooling or automation that made a team measurably faster.
- Experience building applications for on-premise deployment.
- Familiarity with managed backend platforms and AI agent tooling.
- Any prior early-stage startup experience.
- Degree in computer science or a related field.
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