AI/ML Engineer Demand

As a Sr. Eng to Architect on the Agentic System Layer (ASL) team, you will define and drive the technical architecture for CLIENT's 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.

1. 10+ 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).
2. 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.
3. 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/Clienture/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.