About this role
About the Role We are seeking AI Agentic Development Engineers to join and build a new Applied AI team. The role focuses on designing, developing, and deploying rapid prototypes of AI-driven tools and agentic workflows that automate complex tasks and accelerate engineering processes. This is an individual contributor role with a hybrid schedule, aimed at accelerating cross-functional engineering teams. What You'll Do
- Ideate, architect, and build proof-of-concepts (PoCs) for AI-powered engineering tools, multi-agent systems, and automation scripts.
- Partner closely with Product Engineering teams to deeply understand their workflows, identify bottlenecks, and embed AI solutions where they matter most.
- Leverage LLMs, vector databases, and agentic frameworks (e.g., LangChain, CrewAI, AutoGen) to build autonomous workflows capable of reasoning, tool-use, and decision-making.
- Refine and automate multi-disciplinary engineering pipelines within Product Engineering.
- Run rapid experiments: hypothesis → prototype → deploy → evaluate → iterate
- Embrace a fail-fast approach — short cycles, quick learning, and moving on with better information
- Containerize and self-host solutions — taking full ownership from development through deployment
- Evaluate tools and models through hands-on use, not benchmarks alone
- Identify what scales and what doesn't based on real-world deployment behavior
- Document validated patterns that contribute to the team's shared AI use case library
- Think in terms of scale: how do I share my work, knowledge, and practices with others so they can join the mission What We're Looking For
- Minimum of 2+ years of experience in the following:
- AI & Agentic Frameworks: Hands-on experience working with LLMs (OpenAI, Anthropic, open-source models) and orchestration frameworks like LangChain, LlamaIndex, CrewAI, or similar.
- Programming Mastery: Proficiency in Python, TypeScript, or similar languages optimized for fast development and AI integration.
- APIs & Integrations: Strong experience connecting disparate systems via REST APIs, webhooks, and SDKs (e.g., integrating AI agents with GitHub, Jira, Slack, or internal engineering tools).
- Data Foundations: Familiarity with RAG, vector embeddings, vector databases (e.g., Pinecone, Chroma, Milvus), and prompt engineering techniques.
- Workflow Automation Architecture: n8n, LangGraph, CrewAI, ChromaDB, and Docker.
- Ability to make complex and analytical decisions and recommendations to management.
- Strong problem solving/analytical skills, where problems are complex
- Excellent oral & written communication skills
- Strong interpersonal skills
- Conflict resolution & risk escalation skills
- Excellent leadership skills in a team environment
- Experience with the product development process
- Understanding of technical & Nice to Have Compensation & Benefits