Role: Agentic AI Engineer
Location: Oakland, CA (Remote)
We are seeking an experienced agentic AI engineer to design, build, and operationalize enterprise AI solutions grounded in trusted organizational knowledge.
This is a hands-on role for someone who is comfortable moving from use case discovery and solution design through implementation, testing, deployment, monitoring, and continuous improvement. The successful candidate will place equal emphasis on business value, user adoption, responsible AI, engineering quality, and measurable solution performance.
Key Responsibilities
Design, build, and deploy agentic AI solutions, including AI agents, multi-agent workflows, semantic search, grounded conversational assistants, and tool-using AI solutions.
Develop reusable agent components, tools, connectors, orchestration patterns, evaluation assets, guardrails, and reference implementations that accelerate the delivery of future enterprise AI solutions.
Integrate AI solutions with enterprise knowledge graphs, ontologies, semantic models, APIs, data services, content repositories, and business systems to ground outputs and agent actions in trusted, governed enterprise information.
Select and integrate large language models, agent frameworks, retrieval technologies, knowledge platforms, and vendor solutions, making sound build-versus-buy recommendations based on business requirements, enterprise architecture, security, cost, and operational complexity.
Collaborate with enterprise architecture, cybersecurity, privacy, legal, compliance, and AI governance teams to ensure solutions conform to enterprise standards and regulatory obligations.
Mentor engineers and contribute to the broader development of agentic AI engineering capabilities, standards, reusable knowledge, and delivery practices across the organization.
Support continuous improvement of the enterprise agentic AI delivery lifecycle, from opportunity assessment and prototyping through production deployment, operational monitoring, and solution retirement.
Contribute to agentic AI capability roadmaps, platform planning, reference architectures, and long-term enterprise solution delivery strategies.
Qualifications
Bachelor s degree in computer science, software engineering, information systems, data science, or a related discipline is required. A master s degree in a related discipline is preferred.
10+ years of experience in software engineering, AI engineering, solution architecture, or related technical roles, including at least 2 years building and deploying large language model applications or agentic AI solutions.
Proven experience designing, building, and operating production AI applications, preferably including AI agents, tool-using assistants, semantic search, or knowledge-grounded conversational applications.
Hands-on experience with agentic AI or generative AI development frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, AutoGen, or equivalent technologies.
Experience implementing AI application guardrails, access controls, monitoring, observability, and audit mechanisms.
Strong understanding of responsible AI principles, including privacy, security, explainability, transparency, human oversight, bias mitigation, and risk-based controls.
Experience integrating AI applications with enterprise data platforms, content repositories, APIs, data services, and identity and access management capabilities.
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