Applied AI Engineer
Skills
- Strong Python and production service development experience
- Hands-on production experience with LLMs: prompt engineering, tool/function calling, structured output
- Experience with agent frameworks (LangChain, LangGraph, or similar)
- Comfort with async Python, HTTP APIs, and streaming protocols (SSE, webhooks)
- Data validation and schema design experience (Pydantic, JSON Schema)
- Ability to diagnose issues across stack from LLM outputs to infra misconfiguration
- Clear communication and cross-functional collaboration
Responsibilities
- Design, prototype, and ship AI agents that interact with tools, call APIs, and produce structured outputs for real users.
- Build evaluation harnesses and quality scoring (safety, effectiveness, personalization) and iterate based on results.
- Own the full lifecycle from experiment to production: staging, deployment, monitoring, and continuous improvement.
- Optimize reliability, latency, and cost via prompt caching, token budgets, retry logic, and observability.
- Implement integrations and tooling (API clients, Pydantic validation, search over local datasets) used by agents.
- Collaborate cross-functionally with product, mobile, and backend teams to identify high-impact AI opportunities.
Education
- Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience (preferred)
- Relevant professional experience in applied ML/AI and backend engineering
Benefits
- Base salary $215,000–$250,000/year plus equity
- Equity participation alongside base compensation
- Comprehensive medical, vision, dental, and disability insurance
- 401(k) retirement plan
- Remote-first role (eligible across the continental US)
- Monthly health & fitness stipend, mental health platform access
- Flexible PTO and annual learning & development stipend
- Free Future membership and wellness reimbursements
Average salary estimate
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