Software Engineer, AI & Data

The Role

We're hiring a mid-level software engineer with strong TypeScript and Python, data engineering and

applied LLM skills. You'll build backend services, data pipelines and LLM-powered features, then own them in production. This role suits a generalist who is comfortable moving between these areas and wants to go deep in at least one.

What You’ll Do

• Build and maintain TypeScript and Python backend services and REST APIs.
• Design batch data pipelines with orchestration, tests and data quality checks.
• Build LLM features end to end: prompts, retrieval, structured outputs and evaluation, tracking accuracy, latency and cost.
• Turn scanned documents into structured data using OCR and LLMs.
• Containerize, deploy and monitor services in the cloud, and share on-call [rotation details].
• Write tests, review code and document what you build.
• Work with product, operations and data partners to scope work and ship in small, frequent increments.

What We’re Looking For

• 3 to 5 years of professional software engineering experience, or equivalent.
• Production experience with the Required technologies in the tech stack above.
• Has shipped at least one LLM-powered feature to real users, with a way to measure its quality.
• Clear written communication, including explaining technical tradeoffs to non engineers.

Nice to Have

• Experience with an AI-driven SDLC: using coding agents and assistants (e.g., Claude Code, Cursor or GitHub Copilot) across planning, coding, testing and code review.
• Experience handling sensitive data (PII, financial or health records) under compliance programs like SOC 2.
• Small-team experience owning systems end to end, from design through on-call.

Technology Stack

Strength in the required technologies matters most. Nice-to-have technologies are a plus, not a filter.

Required

• Languages: TypeScript and Python (strong), SQL (solid)

• Backend and APIs: REST APIs in Node.js or Python (e.g., Express, NestJS, FastAPI or Django); background jobs and queues

• Cloud and infrastructure: AWS, GCP or Azure; Docker; CI/CD

• Data engineering: Batch pipelines with Airflow, Dagster or dbt; data quality testing

• Applied AI and LLMs: LLM APIs (OpenAI, Anthropic or similar); prompt design; measuring output quality

• Observability: Logging, metrics and alerting for production services

Nice to Have

• Backend and APIs: Event-driven systems (Kafka, SQS or Pub/Sub)

• Cloud and infrastructure: Kubernetes, Terraform, Pulumi

• Data engineering: Snowflake, BigQuery or Redshift; Metabase

• Applied AI and LLMs: RAG and vector search (pgvector, Pinecone); OCR and document AI (Textract, Google Document AI, Azure Document Intelligence)

• Observability: Sentry, PostHog or Datadog

What We Offer

• Annual Salary of $120,000
• Equity
• CrowdHealth Membership Allowance
• Remote flexibility
• 12 weeks paid maternity/paternity leave
• No cap on paid time off