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Tech Stack
Tools & technologiesMicroservicesPythonSQL
About the role
Key responsibilities & impact- Own the AI engine: Design and evolve context architectures (templates, few-shot examples, structured outputs); manage context window limits; optimize for quality and cost; validate schemas and handle edge cases
- Architect and ship agentic workflows: Design agent boundaries, clean tool interfaces, failure handling, and human oversight points; manage agent state across turns; ensure robustness through guardrails and graceful degradation
- Drive AI quality: Define success criteria before shipping; build and run eval sets; catch regressions before users do; analyze failure patterns systematically; iterate on evidence, not gut feel
- Own AI production operations: Trace LLM calls and agent steps across the stack; monitor cost and latency; set SLOs; respond to incidents; establish operational runbooks
- Write solid Python backend code: Build APIs, microservices, and database schemas that support the above; own deployment and on-call for your services
- Raise the engineering bar: Champion clean code, the testing pyramid, and sharp code reviews across the team
Requirements
What you’ll need- 3+ years shipping AI/LLM-powered features in production (not research, not prototypes)
- Hands-on context architecture design: Prompt engineering, structured outputs, schema validation, few-shot design, context window optimization
- Experience building and operating agentic systems: Tool interface design, orchestration patterns, failure handling, agent state management, multi-turn conversations
- Systematic approach to AI quality: Eval sets, success criteria definition, failure pattern analysis, evidence-based iteration
- Production AI observability: Tracing LLM calls and agent steps, cost monitoring, latency tracking, incident investigation
- Proficiency in Python (production-grade, enterprise experience)
- Solid backend fundamentals: APIs, microservices, SQL database design and optimization
- Daily hands-on use of AI development tools (Cursor, Claude Code, Copilot, or similar) — this is a hard requirement
- Fluent English (written and verbal)
- Self-driven, product-minded, no hand-holding needed
- Has owned a non-trivial AI feature or agentic workflow in production for 12+ months — context design, evals, on-call, iteration on real user feedback
Benefits
Comp & perks- Join a small team of passionate engineers dedicated to innovation and excellence
- Work on a product that genuinely improves people's lives and workplace safety
- Experience a startup culture: fast-paced, close collaboration, real influence on key decisions
- Short feedback loops — ship fast, learn fast
- Minimal bureaucracy — focus on what matters: building great software
- AI-first engineering culture — we embrace and invest in AI-augmented development
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
Pythoncontext architecture designprompt engineeringstructured outputsschema validationfew-shot designcost monitoringlatency trackingAPIsmicroservices
Soft Skills
self-drivenproduct-mindedcommunicationevidence-based iterationfailure handlinganalytical thinkingteam collaborationclean code advocacycode reviewincident investigation