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AI Lead Engineer

Talent GroupsUnited States🇺🇸United States

Quick overview

SeniorityMid Senior
Work modeHybrid
LocationUnited States
MicroservicesAWSMLOpsGoogle CloudJavaLLMPythongRPCRESTAzureKubernetesTypeScriptPrompt EngineeringLangChainLangGraphRAGSystem Design

Job description

Job Description:

  • As Sr Eng or Architect on the Agentic System Layer (ASL) team, you will define and drive the technical architecture for agentic AI platform.
  • Day-to-day responsibilities include designing and evolving the architecture for multi-agent orchestration systems, tool-use frameworks, and LLM integration pipelines
  • establishing patterns for agent reliability, observability, and guardrails at production scale
  • leading technical design reviews and producing architecture decision records (ADRs)
  • collaborating with ML engineers and software engineers to ensure platform components are scalable, secure, and maintainable
  • evaluating and integrating emerging agentic AI frameworks (e.g., LangGraph, CrewAI, Semantic Kernel, AutoGen)
  • defining API contracts, data flow patterns, and integration standards across the AI platform ecosystem; mentoring engineers on best practices for building production-grade AI systems.

Top 3 Mandatory Skills and Experience:

  • 13+ years software architecture experience with at least 3 years designing AI/ML platform systems, including hands-on experience with LLM orchestration frameworks (LangChain, LangGraph, Semantic Kernel, or similar).
  • Deep expertise in distributed systems design, microservices architecture, event-driven patterns, and API design (REST/gRPC), with strong proficiency in Python and at least one of Java/Go/TypeScript
  • Production experience building and deploying agentic AI systems or LLM-powered applications at scale, including prompt engineering, tool-use patterns, RAG pipelines, and agent reliability/observability.

Nice to Have Skills:

Experience with Kubernetes/container orchestration, cloud platforms (AWS/Azure/Google Cloud Platform), MLOps/LLMOps tooling, vector databases (Pinecone, Weaviate, pgvector), knowledge graphs, airline/travel domain experience, TOGAF or similar architecture certification, experience with multi-agent system design patterns and agent evaluation/benchmarking frameworks.

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