- Company Name
- Lyft
- Job Title
- Software Engineer, Developer Experience - AIIT
- Job Description
-
Job title: Software Engineer, Developer Experience – AI Infrastructure
Role Summary: Design, build, and maintain scalable AI infrastructure that powers large language model (LLM) integration for developers. Deliver frameworks, orchestration, observability, and cost‑management tools to enable AI‑driven coding, testing, documentation, and incident response across the organization.
Expectations: • Deliver high‑quality, production‑ready AI infrastructure components within sprint timelines.
• Drive cross‑team initiatives and lead incident response for AI systems.
• Mentor peers and promote responsible AI practices.
Key Responsibilities: • Architect and implement LLM gateways, prompt managers, vector databases, and agent orchestration frameworks.
• Build intelligent agents and automation to streamline developer workflows (code generation, testing, review, documentation, incident response).
• Develop centralized workflow services and UI tools for easy use.
• Implement observability, monitoring, and cost‑tracking for AI usage.
• Plan and execute end‑to‑end cross‑team AI projects, including evaluation pipelines and safety guardrails.
• Partner with ML platform, infrastructure, and product teams to debug, design, and scale AI solutions.
• Establish best practices for LLM integration, prompt engineering, Retrieval‑Augmented Generation (RAG), and agent development.
• Write clean, well‑tested, maintainable code and comprehensive technical documentation.
• Lead on‑call rotations and incident post‑mortems for AI infrastructure.
• Mentor engineers on AI infrastructure and responsible AI development.
Required Skills: • 3+ years in software development, distributed systems, or infrastructure engineering.
• Hands‑on experience with LLM APIs (OpenAI, Anthropic, etc.) or AI infrastructure platforms.
• Proficient in Python and/or Go; experienced with Kubernetes, containerization, and cloud infrastructure.
• Knowledge of vector databases, embeddings, and RAG architectures.
• API design, SDK development, and building developer‑facing frameworks.
• Expertise in observability, distributed tracing, metrics, and monitoring.
• Strong understanding of LLM capabilities, prompt engineering, and AI safety considerations.
• Excellent problem‑solving, communication, and documentation skills.
Optional / Bonus: • Experience building AI agents or multi‑agent systems (LangChain, LangGraph, ReAct).
• Fine‑tuning, model evaluation, and AI safety guardrail implementation.
• Front‑end/UI design knowledge.
• Background in developer tools or platform engineering.
Required Education & Certifications: • Bachelor’s degree in Computer Science, Engineering, or related field, or equivalent experience. • No mandatory certifications required; relevant industry credentials (e.g., Kubernetes, cloud platforms) are a plus.