Principal AI Engineer

Hiring a Staff/Principal AI Engineer to lead enterprise-scale agentic AI implementations for Fortune 500 clients.
This is a hands-on engineering role focused on designing and shipping autonomous, tool-calling AI systems — agents that reason over enterprise context, invoke real systems through secure interfaces, and operate reliably at scale under strict latency, cost, and governance constraints.

You will own these systems end to end: the data pipelines feeding them, the backend services around them, the agent orchestration layer, the evaluation harness that keeps them honest, and the cloud infrastructure they run on. We are looking for engineers with genuine software engineering and data science depth who have taken agentic systems all the way to production.
What We're Looking For

Engineering foundation
8–14 years of software engineering experience, with strong hands-on large-scale Python
Working depth in at least one systems or backend language — Go, Rust, Java, or C/C++ — and the judgment to know when to reach for it
Strong data structures and algorithms.
Strong understanding of APIs, microservices, and system design
Hands-on experience building and operating data pipelines and production-grade distributed systems.

Agentic AI and LLMs
2+ years of hands-on LLM engineering, with at least couple agentic system you designed and took to production
Production experience with agent frameworks — LangGraph, Google ADK, CrewAI, Claude Agent SDK, or equivalent — and the fluency to move between them as the ecosystem evolves
Experience building MCP (Model Context Protocol) servers and tool-calling interfaces
RAG from first principles: chunking strategy, embeddings, vector and hybrid retrieval, reranking, and response validation
Strong experience with vector databases (Milvus, Pinecone, Weaviate, FAISS, etc. or cloud equivalents)
Design of guardrails and reliability patterns — validators, policy checks, self-correction loops, deterministic fallbacks, circuit breakers, and rollback paths