semantic-kernel jobs in San Diego

Build production AI features and workflows powered by large language models, including retrieval-augmented generation (RAG), agentic orchestration, and tool/function calling integrations. You will design and implement scalable microservices in Python or Java that connect foundation model APIs to business data and internal systems, with responsibility for AI quality, evaluation, observability, and safe deployment on AWS.…See more Collaborate with cross-functional teams to prototype solutions, measure outcomes, and move proven capabilities into production while maintaining reliability, security, and auditability.

Chief AI Subject Matter Expert leading the development of intelligent data processing pipelines, NLP systems, and AI-enabled dashboards for defense applications. The role requires 15+ years of experience with generative AI, LLMs, and agent-based development workflows, including hands-on use of tools like GitHub Copilot and Claude for code generation and automation.…See more Responsibilities include prototyping emerging AI tooling, mentoring engineering teams on AI integration, designing secure production AI solutions, and identifying opportunities to accelerate the software lifecycle through AI and automation. Must demonstrate expertise in LLM APIs, RAG architectures, vector databases, prompt engineering, and AI-specific security considerations in classified/sensitive environments.

This Technical Lead role focuses on architecting, developing, and deploying production-grade Agentic AI solutions on AWS using .NET/C#. The ideal candidate will have hands-on expertise in LLMs, generative AI, RAG, prompt engineering, and agent frameworks (LangChain, LangGraph, Semantic Kernel, AutoGen), combined with strong .NET enterprise development and AWS cloud-native skills.…See more Responsibilities include taking AI solutions from POC to production, designing microservices and REST APIs, and ensuring AI evaluation, monitoring, observability, and governance. Technical leadership, stakeholder management, and system design fundamentals are essential.

A Forward Deployed AI Engineer who builds and deploys production AI/ML and Generative AI applications, particularly agentic workflows and RAG systems integrated with enterprise data and business systems. The role requires 6+ years of software/ML/AI engineering experience, advanced Python proficiency, hands-on expertise with LLMs, modern GenAI frameworks (LangChain, LangGraph, LlamaIndex), and cloud platforms (Azure, AWS, GCP).…See more You'll own solutions from prototype through production, working directly with product and business stakeholders to identify where AI creates value, troubleshoot integration issues, and drive continuous improvement.

Director-level role leading AI/ML engineering strategy and execution across Optum's healthcare technology organization. You will define the roadmap for LLM engineering, generative AI systems, and agentic workflows; lead and mentor a team of 10+ AI/ML engineers, software developers, and MLOps specialists; architect scalable multi-cloud AI solutions spanning AWS and Azure with .NET/C# services; and champion ethical AI governance and production-grade model deployment practices.See more

Lead the design, development, and operation of Qualcomm's enterprise AI platform, supporting agentic AI, model lifecycle management, and multi-cloud ML/inference infrastructure. Own core platform services including identity/RBAC, secrets, service meshes, observability, vector stores, and model gateways across on-prem GPU clusters and managed cloud services.…See more Manage a ~10-engineer global team (platform, SRE, MLOps/LLMOps), drive incident response and continuous improvement, and partner with product and security teams on AI governance and high-impact use cases.

Senior AI Subject Matter Expert responsible for developing intelligent data processing and NLP pipelines, AI-enabled dashboards, and proofs-of-concept for AI use cases. The role requires 7+ years of professional experience with advanced expertise in LLM APIs, RAG architectures, agent-based development, generative AI coding tools, and secure AI deployment patterns.…See more Responsibilities include prototyping emerging AI developer tooling, mentoring engineering teams on generative AI workflows, and identifying software lifecycle areas that can be accelerated through AI and automation. The candidate must critically evaluate AI-generated code for correctness and security, understand AI-specific security risks across the full SDLC, and scope requirements for engineering solutions that meet business challenges with measurable outcomes.

Build production AI features and services using foundation model APIs, retrieval-augmented generation (RAG), and agentic workflows. You will implement scalable microservices in Python or Java, develop evaluation and quality frameworks for AI systems, and collaborate across teams to integrate AI capabilities into enterprise workflows.…See more The role requires hands-on applied AI experience, strong backend or platform engineering skills, and familiarity with vector databases, LLM orchestration tools, and cloud infrastructure.

Design and build production AI solutions including copilots, agents, RAG applications, and workflow automations on Azure OpenAI, Claude, and Microsoft platforms. Write custom code in Python, JavaScript/TypeScript, or C# and leverage low-code platforms like Power Automate and Logic Apps where appropriate, following solid engineering practices (version control, testing, CI/CD, AI output evaluation).…See more Integrate solutions with enterprise systems and APIs with security-first design, own projects end-to-end from deployment through adoption and improvement, and work with security, architecture, governance, and compliance teams to ensure production readiness. Communicate clearly to both technical and business audiences, document designs, and coach teammates on AI capabilities, limits, and risks.

Senior Microsoft Forward Deployed Engineer who will design, build, and deploy GenAI/LLM-powered solutions for government clients, translating business problems into production-grade AI systems. The role requires 7+ years of software/data engineering experience, 1+ years hands-on with GenAI/LLM solutions, and deep expertise in Microsoft Azure (AI Foundry, OpenAI, AI Search), Python/TypeScript/C#, and Copilot extensibility.…See more You will lead project workstreams, work directly with client technical teams in fast-paced environments, and mentor others while building reliable, maintainable, well-documented code. 50% travel required.

Design, develop, and deploy end-to-end generative AI solutions including GenAI agents, LLMs, and applications to solve complex business challenges. Build data pipelines, design APIs for AI accessibility, and collaborate with cross-functional teams (developers, data scientists, business) to implement enterprise GenAI solutions.…See more Requires 4+ years of full-stack application development (Java, Python, JavaScript) and 3+ years with data structures, algorithms, and data stores. Stay current with AI research and communicate technical concepts to non-technical stakeholders.