Policybot is building a focused data platform to organize healthcare payer policy data, and you will be at the helm of data ingestion, AI-powered processing, and platform development as a founding engineer. Based in New York City, this hybrid role blends hands-on engineering with end-to-end ownership of the data stack, while collaborating with a small, ambitious team to define the future of healthcare data infrastructure.
Responsibilities
- Design ingestion pipelines that convert messy, unstructured payer policies into structured, queryable objects
- Define evolving data schemas that adapt without breaking downstream consumers, and prioritize data quality
- Leverage AI to scale the data ingestion pipeline to cover hundreds of health insurers
- Build pipelines for auditability, traceability, and explainability
- Develop and refine LLM-powered data pipelines that extract and structure data elements from raw text
- Create systems to evaluate and benchmark LLM-driven features, including evaluation harnesses, QA workflows, and human validation loops
- Improve search capabilities by designing and implementing Retrieval-Augmented Generation pipelines over healthcare policy documents; experiment with embeddings, vector databases, and fine-tuning strategies
- Rapidly prototype, determine what works, productionize successful ideas, and discard the rest
- Navigate ambiguity by asking questions until the problem is clearly understood
- Prioritize data quality and usability over flashy features, making thoughtful tradeoffs
- Demonstrate end-to-end product ownership to ensure new technologies are integrated into the company and product
- Leverage AI to scale work and improve organizational efficiency
Requirements
- 5+ years experience building data-heavy backend systems
- Proven track record with data pipelines and data-driven software products
- Strong proficiency with Python, SQL, PostgreSQL, and modern cloud infrastructure (AWS preferred)
- Experience building AI-native products, including LLMs, RAG, embeddings, prompt engineering, hallucination mitigation, data labeling, evaluations, and monitoring
- Product-oriented mindset with the ability to weigh technical changes against business value
- Fluency in designing and evolving data models, schemas, and APIs for long-term maintainability
- Demonstrated ability to take ambiguous problems, define requirements, map the ideal architecture, and execute end-to-end
- Experience designing and building backend infrastructure for scalability
- Ability to manage, plan, and run projects independently
- Thrives in fast-paced, ambiguous environments
Technologies
- Python
- SQL
- PostgreSQL
- AWS
- Snowflake
- Terraform
- TypeScript
- React
- FastAPI
Benefits
- Founding equity
- Medical coverage
- 401K
- Learning stipend
- Unlimited PTO
Bonus Points
- Exposure to healthcare, payer/provider data, or health tech
- Prior exposure to startups, research teams, or high-paced environments
- Willingness to dive into new tools, frameworks, and AI systems quickly
- Experience front-end development (TypeScript/React)
- Experience building high-throughput applications with FastAPI
- Experience working with data warehouses (e.g., Snowflake)
- Exposure to Infrastructure-as-Code (Terraform) and container orchestration
Why Join Policybot
You will join a compact, ambitious team where you shape the architecture, culture, and velocity of the engineering organization from day one. You’ll work directly with the founders to tackle some of healthcare data's toughest problems and experiment with cutting-edge AI tools to apply them to real-world challenges. Your work will contribute to systems that form the backbone of a new category of data infrastructure in healthcare.
Application Question(s)
This position requires on-site attendance. Do you currently live within commuting distance of New York City?
Job Type
Full-time
Pay
USD 130,000 - 160,000 per year
Work Location
Hybrid remote in New York, NY 10001
Experience
- professional engineering: 3 years (Required)
- professional Python programming: 2 years (Required)
