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Lead AI Engineer

METANLYTICS LLCSanta Clara, CA🇺🇸United StatesPosted 12 Aug 2026

Quick Overview

Work Type
On Site
Level
Mid Senior

Job Description

Lead AI Engineer
Location: Santa Clara, CA – Onsite
Duration: 12 Months
No. positions: 2  
Client: Applied Materials (Any visa )
 
 
 
Lead AI Engineer
 
Lead AI Engineer to architect, lead, and deliver production-grade Agentic AI solutions for enterprise use. The individual will drive solution design, guide development teams, build multi-agent AI systems, and ensure scalable, secure, and reliable deployment in production environments.
Scope of Work
  • Lead architecture and solution design for Agentic AI applications.
  • Build and oversee development of AI agents and multi-agent systems using LangGraph and LangChain.
  • Design and optimize AI workflows across multiple LLMs (GPT, Claude, Llama, etc.).
  • Guide engineering teams and establish development best practices.
  • Develop enterprise integrations, APIs, and event-driven AI services.
  • Drive deployment, operationalization, and scalability of AI applications.
  • Coordinate with platform, security, data, and product teams to ensure successful delivery.
  • Leverage AI-assisted development tools such as Claude Code and Codex to accelerate engineering productivity.
Must-Have Skills
  • 5+ years of experience in AI/ML.
  • 1+ years of experience building Agentic AI solutions.
  • Strong expertise in Python and modern software engineering practices.
  • Hands-on experience with LangGraph, LangChain, LLMs, and prompt engineering.
  • Experience architecting and deploying enterprise AI applications.
  • Familiarity with Azure AI Foundry, AWS Bedrock, Google Gemini Enterprise, or similar platforms.
  • Strong understanding of APIs, event-driven architectures, CI/CD, and cloud deployment.
  • Proven ability to lead technical initiatives and drive solution delivery.
  • Excellent communication, stakeholder management, and problem-solving skills.
  • Experience with enterprise data integration and AI application deployment.
Good-to-Have Skills
  • Databricks
  • MLOps / LLMOps
  • Enterprise AI Governance and Security
  • AI Monitoring and Observability
  • Enterprise AI Architecture and Strategy
 
 
 

Skills

AWS
MLOps
Azure
Databricks
GPT
Python
Stakeholder Management

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