Lead AI Engineer
Job in
Santa Clara, Santa Clara County, California, 95053, USA
Listed on 2026-07-20
Listing for:
Sapear Inc
Full Time
position Listed on 2026-07-20
Job specializations:
-
Software Development
AI Engineer (Applied/Software), Software Architect, Machine Learning/ ML Engineer, DevOps
Job Description & How to Apply Below
Lead AI Engineer
Location:
Santa Clara, CA (Onsite Mon to Fri)
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 Lang Graph and Lang Chain.
- 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.
- 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 Lang Graph, Lang Chain, 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.
- Databricks
- MLOps / LLMOps
- Enterprise AI Governance and Security
- AI Monitoring and Observability
- Enterprise AI Architecture and Strategy
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