Role: Lead AI Engineer
Duration: 6-12+ Months Contract
Location Santa Clara, CA (Onsite)
Must Have Skills
Skill 1 Lead architecture and solution design for Agentic AI applications
Skill 2 Design and optimize AI workflows across multiple LLMs (GPT, Claude, Llama, etc.).
Skill 3 Leverage AI-assisted development tools such as Claude Code and Codex to accelerate engineering productivity
Good To have Skills
Skill 1 Strong expertise in Python and modern software engineering practices
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
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