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Tier-1 brand, mid-level experience, and metro location increase applicant competition.
Specialized agentic AI, LangChain, and MLOps requirements limit cross-industry transferability.
Multiple explicit years and mandatory tools (LangChain, GCP, Kubernetes, MLOps) increase filter strictness.
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Lead design, development, and deployment of advanced AI agents (using LangChain, LangGraph) that automate decision-making within claims lifecycle.
Architect and operate scalable AI/MLOps solutions on Google Cloud Platform impacting millions of users, including managing AI model integration, observability, and production reliability.
Manage and mentor a technical team, define engineering metrics (SLA/SLO/SLI), and collaborate with cross-functional teams to translate business requirements into technical roadmaps and solutions.
Bachelor's degree or equivalent experience in relevant field.
5+ years software engineering experience with technical leadership in complex, scalable systems.
1+ years experience in dedicated AI/ML roles including model integration, MLOps and AI problem-solving.
1+ years experience with LangChain, LangGraph, or similar agentic AI frameworks; 2+ years experience with Google Cloud Platform AI/ML services; 3+ years with Kubernetes workloads; proficiency in Python and JavaScript/TypeScript/Java; experience with containerization, IaC and CI/CD tools.
Proven ability to architect and deliver production-grade AI/agentic systems at enterprise scale using advanced AI frameworks and cloud-native technologies.
Experienced technical leader capable of managing teams, mentoring engineers, and driving complex end-to-end AI software projects in collaborative environments.
Practical AI innovator who balances bleeding-edge research with stable, scalable software delivery, familiar with GenAI models (Gemini, ChatGPT, Claude) and AI code assistant tools like GitHub Copilot.