vector-embeddings jobs in San Diego

Principal AI Platform Engineer leading enterprise AI infrastructure strategy and governance at the platform boundary. Responsible for implementing and maintaining Bedrock Guardrails and Microsoft Purview DLP controls, managing AI vendor relationships with Microsoft and AWS, producing governance artifacts and runbooks, and leading internal AI adoption through community building and enablement.…See more Requires 7–10 years of cloud/DevOps experience with hands-on production expertise in AWS Bedrock (Agents, Knowledge Bases, Guardrails) and Microsoft 365 Copilot deployment in enterprise environments, including data integration, RAG architecture, and AI security controls.

Lead the design, deployment, and governance of an enterprise AI platform integrating AWS Bedrock, Microsoft 365 Copilot, and structured/unstructured data sources. Act as the primary technical authority for AI infrastructure, RAG architecture, security controls, and AI adoption across business units, with responsibility for platform budget, vendor contracts, and internal capability building through mentoring and community-of-practice leadership.…See more Requires hands-on production experience with Bedrock (Agents, Knowledge Bases, Guardrails), M365 Copilot enterprise deployment, and proven ability to operate as a solo platform owner in a matrixed organization without direct reports.

Staff Software Developer who will design, develop, and maintain AI-enabled knowledge management and decision-support platforms for environmental and engineering applications. Responsibilities include building data ingestion workflows, implementing retrieval-augmented generation (RAG) systems with vector embeddings and semantic search, developing backend services and APIs, creating secure web-based UIs, and working with cloud services (Azure AI Search, Blob Storage, PostgreSQL).…See more The role requires strong software development skills demonstrated through a public code portfolio, familiarity with LLMs and prompt engineering, and the ability to collaborate across technical teams to translate project needs into practical features.