Senior AI Engineer

🚀 What You'll Own

• AI Feature Development: Take ambiguous requirements and turn them into well-reasoned, production-grade implementations end-to-end.
• Agentic Workflows: Design multi-step, tool-using agents that orchestrate LLM calls, APIs, and platform data. Architect systems that plan, reason, act, and recover from failures gracefully.
• LLM Integration: Integrate and critically evaluate LLMs across providers (AWS Bedrock with Anthropic Claude, Azure OpenAI, and others) to select the right approach per use case.
• Prompt Engineering and Evaluation: Write, version, and evaluate prompts systematically. Build pipelines that catch regressions before they reach users.
• AI Engineering Standards: Establish patterns, tooling choices, and best practices the wider engineering team can build on as AI work scales.

🫶🏽 Our Ideal Senior AI Engineer

Must-Have

• 4+ years of software engineering experience, with at least 1–2 years shipping AI/LLM features to production.
• Strong hands-on experience integrating LLM APIs (OpenAI, Anthropic, or equivalent) in a Node.js/TypeScript codebase.
• Proven experience designing agentic workflows: multi-step reasoning, tool use, state management, and failure handling. You build systems, not wrappers.
• Product startup background; comfortable owning outcomes and navigating ambiguity.

Strong Plus

• LangChain, LangGraph, or similar orchestration frameworks.
• RAG architectures and vector databases.
• LLM observability, prompt security, and hallucination mitigation in production.