RouteGenie

Role Description You'll work with and bring opinions on choosing between the following: - LLM Providers & APIs: Anthropic Claude (primary), OpenAI, AWS Bedrock - Local / Self-Hosted LLMs: Ollama, LM Studio, llama.cpp, vLLM; open-weight model families (Llama, Qwen, Mistral, etc.) - Agent Frameworks: LangChain / LangGraph, LlamaIndex, OpenAI Agents SDK, or equivalent - Retrieval & Knowledge: Vector databases (Pinecone, Weaviate, pgvector); RAG, cache-augmented generation, tool-based agentic retrieval, GraphRAG, hybrid approaches - Voice AI: ElevenLabs, VAPI, LiveKit, Deepgram - LLM Observability & Eval: LangSmith, Braintrust, Phoenix, Helicone, or similar - AI-Assisted Development: Claude Code - RouteGenie Stack: Python, Django, PostgreSQL, Angular, TypeScript Qualifications - Experience: 3+ years of software engineering experience. - Production AI: 1+ year hands-on experience with production LLM / AI features shipped to real users (not prototypes or coursework). - Languages: Strong Python skills; comfort with TypeScript. - Frameworks: Hands-on experience with at least one agent framework and multiple retrieval/context-augmentation approaches. - APIs: Production experience with major LLM provider APIs from our Tech Stack. - Architectural Judgment: Sound judgment on AI architecture choices. Ability to select the right model and execution environment against cost, latency, accuracy, and data-residency constraints. - Quality Measurement: Demonstrated experience measuring AI feature quality in production. - Communication: Working professional English; strong async written communication for collaboration across Mexico, Europe, and US time zones. Requirements - Voice AI: Experience with Voice AI. NEMT dispatch and customer-service flows are voice-heavy, and voice agents will be a major product surface. - Regulated Data: Experience in a healthcare or regulated-data context (HIPAA, PII/PHI handling). - Self-Hosting: Local / self-hosted LLM experience running open-weight models on-prem or in a VPC. - Anthropic Ecosystem: Claude API / Anthropic SDK experience — including Claude-specific patterns. Preferred (Nice-to-Have) - LLM observability / eval tooling experience (LangSmith, Braintrust, Phoenix, Helicone, or similar). - Cost and latency optimization at LLM scale (prompt caching, model routing, token budgeting). - Traditional ML / data science background (model training, feature engineering, evaluation methodology). - Django / PostgreSQL background. - Multi-tenant SaaS experience. - Open-source AI contributions or public agent projects.