Database engineer • sunnyvale ca
Job Description<br /> Must Have Technical/Functional Skills:<br /> • 5+ years of experience in AI/ML.Strong expertise in Python and modern software engineering practices.Hands-on e... Show more
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Data Engineer</b> <div><b>Location:</b> Sunnyvale, California (Onsite)</div> <div><br /> <b>Contract:</b> 6 12+ Months</div> <div&g... Show more
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Title: Technical PM (Database Operations)<br /> Location: Sunnyvale, CA/Onsite<br /> Duration: Full Time<br /> Client: Confidential<br /> Salary Range: $80000-$140000 a year... Show more
Software Engineer II - Test Engineer This role has been designed as ''Onsite' with an expectation that you will primarily work from an HPE office.Who We Are: Hewlett Packard Enterpris... Show more
The average salary range is between $ 100,425 and $ 240,000 year , with the average salary hovering around $ 129,200 year .
The average salary range is between $ 110,000 and $ 177,645 year , with the average salary hovering around $ 131,215 year .
Job Description
Must Have Technical/Functional 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.
Roles & 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.
Good-to-Have Skills
• Databricks
• MLOps / LLMOps
• Enterprise AI Governance and Security
• AI Monitoring and Observability
• Enterprise AI Architecture and Strategy
