AI Engineer — Agentic Systems

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Role: AI Engineer — Agentic Systems
Location: Austin, TX (Fully Onsite)
Role Summary:
We are hiring an AI Engineer to 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.
This is an ideal role for an engineer with a strong Python and ML foundation who has already shipped LLM or RAG applications and now wants to go deeper into orchestration,
Required Qualifications:
3–5 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), and comfort writing queries against enterprise schemas.
Experience containerizing and deploying services with Docker and shipping through CI/CD on a major cloud (Azure, AWS, or GCP).
Solid grounding in ML fundamentals and familiarity with PyTorch, TensorFlow, or HuggingFace Transformers.
Clear written and verbal communication, and the judgment to escalate when a problem is under-specified rather than guessing.
Preferred Qualifications:
Experience building or consuming Model Context Protocol (MCP) servers, or comparable agent tool-integration layers.
Production experience with multi-agent or agentic workflow systems, including human-in-t