AI Engineer — Agentic Systems

About the role

Design, build, and operate agentic AI systems - LLM-powered agents that reason over enterprise data, call tools, and execute multi-step workflows end to end.

Tasks

• Develop production Python services and APIs for agent and model inference using FastAPI, containerized with Docker and deployed through standard CI/CD pipelines.
• Apply MLOps and LLMOps practices including version control

Requirements

• 5+ years of professional software, ML, or data engineering experience, including at least 1 year building LLM-based or GenAI applications.
• Strong Python engineering skills - not just notebooks. Production code, testing, packaging, async patterns, and API development with FastAPI or similar.
• Hands-on experience with at least one LLM orchestration framework (LangChain, LangGraph, LlamaIndex, Semantic Kernel, or an equivalent) in a shipped application.
• Demonstrated experience building RAG systems: embeddings, vector stores (e.g., FAISS, pgvector, Pinecone, Chroma), and retrieval quality tuning.
• Practical command of prompt engineering, structured output, function/tool calling, and context-window management.
• Working knowledge of SQL and cloud data platforms (Snowflake, Databricks, or equivalent), a

Pay

• $65/hr on C2C max

Location

• Austin, TX