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Spectraforce

Lead AI Engineer

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What they do

An Artificial Intelligence Engineer develops, tests, and deploys artificial intelligence models. May work closely with data software engineers and data professionals to train and implement AI models into existing systems or develop new applications.

$160,491 / year median in California

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Job Description

Position:
Lead AI Engineer Location:
Santa Clara, CA Duration:
6
Months Job Description:
The 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.
Responsibilities:
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
Required:
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.
Preferred:
Databricks MLOps/LLMOps Enterprise AI Governance and Security AI Monitoring and Observability Enterprise AI Architecture and Strategy