Senior Staff AI Data Engineer, Stellar Health
$250-280k
+ Equity
Incentive program for health providers
Be an early applicant
Incentive program for health providers
201-500 employees
Be an early applicant
$250-280k
+ Equity
201-500 employees
Company mission
To improve the quality of care and affordability of healthcare for millions of patients in the United States.
Role
Who you are
- 8+ years across data platform, ML platform, or developer-tooling - including time as the senior technical voice for a major data/ML/AI surface
- Production experience architecting LLM systems: agents, evals, RAG, MCP, tool use, multi-step workflows, and the failure modes of each
- Strong dbt + cloud warehouse (Snowflake preferred) chops; opinionated about semantic layers and metadata
- Track record of driving wide-team consensus on technical direction - not just shipping, but getting other teams to adopt the pattern
- Comfortable communicating externally: blog posts, talks, OSS contributions, customer-facing thought leadership
- Bonus: Claude Code / Agent SDK, healthcare/claims data, prior 0→1 platform builds
- Architect-mentor, not solo IC. Your impact is measured in what the whole analytics org can do, not just what you ship
- Equally credible in a strategy conversation about where AI takes our analytics next and in developing a new data model the following day
- Decisions have direct, long-term consequences for Stellar's ability to operate on its data
What the job involves
- Stellar Health is hiring a Senior Staff AI Data Engineer to lead how AI transforms analytics and reporting, and to evolve the data architecture that makes it work
- You'll own, drive, and contribute to two key components of our analytics strategy
- The first is AI for analytics and reporting, end to end: strategy, tool selection, administration and architecture, semantic and context layers, and governance. The second is our data architecture
- You'll lead the thinking on how it and our models need to evolve to support these use cases, and contribute to the dbt + Snowflake work to get there alongside our analytics engineers
- Together they serve one goal: compress time-to-insight, and improve the quality of the insights themselves
- Set the strategy for how AI reshapes analytics, reporting, and self-serve data access at Stellar: where it goes first, what it replaces, what it unlocks, and how we sequence it
- Own tool selection, administration, and architecture, including Claude on Snowflake, MCP servers, skills, agent workflows, and IDE integrations, along with the reliability and scaling limits as usage grows
- Design the eval and guardrail systems that catch regressions before they ship and give the team confidence in agent output for high-stakes reporting
- Define how analytics use cases get proposed, governed, and shipped, so AI access to our data is both impactful and controlled
- Debug the hairiest failures, including the agent problems that look like LLM problems but are actually data modeling, metadata, or system-design problems
- Build for futures we can't fully predict: new agent patterns, new tools, new business questions, new regulatory constraints
- Be the role model and mentor for AI-assisted analytics across analytics engineers, analysts, and other engineers. Identify what's worth sharing externally and lead the content and communication around it
- Work alongside the analytics engineering team to extend and refine the dbt + Snowflake models that serve reporting, analytics, and AI consumption, bringing particular attention to the structure, grain, and documentation agents require for accuracy, not only what a human analyst can navigate
- Inform standards for how models, metrics, tests, documentation, and lineage are structured, and build the consensus that gets them adopted team-wide
- Lead the semantic and context layers: metric definitions, business context, and the metadata that makes both dashboards and agents trustworthy, developed with the analysts and engineers who rely on them
Our take
A problem in healthcare is little thought is given to the doctors and staff who coordinate all of the daily patient workflow, such as historical claims, pharmacy requests, lab work, testing and billing. Stellar Health aims to drastically reduce these 'chores' through a cloud-based platform on which primary care providers can offer value-based care through real-time information updates about patients.
The point-of-care workflow platform also strives to close the incentive gap between payors and care providers by helping practitioners earn more revenue for keeping patients healthy, rather than simply charging for procedures and treatments. While Stellar Health faces stiff competition from major players such as Siemens Healthcare and AthenaHealth, it has already made great ground in the market with over 1.1M patients across 37 states.
The company has secured significant investment from Primary Venture Partners and Point 72. This funding and its growing revenue are being put towards further scaling its operations and accelerating its product development. Operating in a rapidly growing industry which reached a value of over $4 billion in 2025, Stellar Health is in a good position for future growth and success.
Kirsty
Company Specialist at Welcome to the Jungle
Insights
-3% employee growth in 12 months
Company
Funding (2 rounds)
Sep 2021
$60m
SERIES B
May 2020
$10m
SERIES A
Total funding: $70m
Company benefits
- Medical, dental, and vision benefits: With coverage starting on your first day of employment
- Collaborative and inclusive culture: Even though we are virtual right now, we are committed to having fun as a team on a regular basis. Virtual magicians, game nights, outdoor happy hours and team picnics
- Generous paid time off policy: We follow a "self managed" PTO philosophy. Take time when you need it
Company HQ
Union Square, New York, NY
Leadership
Michael Meng
(Co-Founder & CEO)Studied Business Adminstration, Finance and Accounting at the University of Michigan, before obtaining an MBA from Wharton School, University of Pennsylvania. Started out as an Investment Banking Analyst at Lazard Freres. Served as Principal at Apax Partners, and currently sits on the board of the Global Language Project, CUNY Graduate School of Public Health and Health Policy and Medicomp Inc.
Octavian Costache
(Co-Founder & CTO)Obtained a Masters in Computer Science and AI from the University POLITEHNICA of Bucharest. Started out as a freelance Software Engineer, before joining Google as a Senior Software Engineer in 2005. Was a HackStar at TechStars in 2012. Co-founded Spring Inc. in 2013, and Stellar Health in 2018.
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