autogen jobs in San Diego

Build and deploy production-ready AI solutions using LLM orchestration platforms (LangChain, LangGraph, CrewAI, n8n) and agentic workflows that integrate with existing data infrastructure like Snowflake. Develop sophisticated prompt engineering and RAG systems with vector databases, conduct independent data analysis to identify AI opportunities, and translate technical work into clear insights for leadership.…See more Move solutions from concept to deployed, maintainable tools with proper documentation and intuitive interfaces. Collaborate cross-functionally with data scientists, analysts, and stakeholders to drive organizational impact.

This Staff AI Engineer role focuses on architecting and implementing secure, scalable frameworks for autonomous AI agents at enterprise scale. The engineer will lead the technical roadmap for agent management—from provisioning and orchestration to compliance and retirement—while ensuring AI agents are secure by design with built-in visibility and guardrails.…See more The role requires 8+ years of software architecture and backend systems experience, deep knowledge of autonomous agent frameworks (LangChain, AutoGen, CrewAI), and expertise in cloud infrastructure (AWS, Azure, GCP) and Kubernetes. You'll collaborate cross-functionally with researchers, platform engineers, and product teams to bring agentic AI capabilities to production while establishing best practices for agent safety, observability, and ethical deployment.

Staff Engineer or Architect role focused on building and orchestrating AI agents in a compliance-heavy, globally regulated environment. You will troubleshoot novel failures across models, tools, and infrastructure; set technical vision; and leverage LLMs, RAG, tool use, and agent frameworks (LangGraph, CrewAI, AutoGen) in production systems.…See more Requires 8+ years of software engineering experience, hands-on LLM and agent-framework work, end-to-end ownership, and demonstrated ability to use AI agents effectively in your own workflow while maintaining accountability and clear mental models of system behavior.

Design and build AI agents and full-stack web applications that automate enterprise workflows, with expertise in agentic AI frameworks, LLM orchestration, and generative AI integration. Architect a multi-agent platform enabling PM and engineering agents to exchange plans and context, while developing backend services in C#/.NET/Python/TypeScript and modern Angular/React frontends that connect to enterprise systems like Jira, Microsoft 365, and SQL/NoSQL databases.…See more Define agentic engineering standards including tool contracts, prompt management, guardrails, and agent evaluation. Requires hands-on experience with LLM application development, RAG, tool calling, prompt engineering, agentic runtimes (LangGraph, AutoGen, n8n), and full-stack enterprise application development on AWS or Azure.

Design and build AI agents that automate workflows within a multi-agent platform, enabling PM and engineering agents to exchange plans and context over shared program data. Develop full-stack web applications with generative AI functionality—conversational interfaces, natural-language querying, automated summarization, and in-context recommendations—using C#, .NET, Python, TypeScript, Angular/React, and integrations with Jira, Microsoft 365, Confluence, and SQL/NoSQL stores.…See more Define agentic engineering standards including tool contracts, MCP servers, prompt management, memory, guardrails, human-in-the-loop approval, and evaluation harnesses. Requires hands-on experience with LLM application development, agentic runtimes like LangGraph or AutoGen, full-stack enterprise development, and cloud deployment on AWS or Azure.

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.

Build and test agent behavior for an AI-driven service, including test case design and evaluation checks distinct from traditional software testing. Support data ingestion pipelines using AWS and BigData tools (PySpark, Airflow), collaborate with product and senior engineers to ship features, and contribute to production support (monitoring, alerting, incident response).…See more Requires 1–2 years of software engineering experience, a Master's in Computer Science or related field, proficiency in Python or another backend language, SQL/NoSQL fundamentals, basic REST API design, and hands-on experience with at least one LLM project (tool calling, chaining, retrieval, or multi-step coordination). Self-directed learner excited about AI tooling and focused on shipping end-to-end products.

This Staff AI Engineer role focuses on architecting and implementing secure, scalable frameworks for autonomous AI agents at enterprise scale. You'll lead the technical roadmap for agent management—from discovery and provisioning through task orchestration—while ensuring safety, compliance, and governance by design.…See more Working cross-functionally with product, platform, and research teams, you'll build foundational infrastructure for multi-agent collaboration, memory management, and extensibility, driving adoption across the enterprise. The role requires 8+ years in software architecture, backend systems, and Kubernetes/AI infrastructure, with deep expertise in LLM frameworks (LangChain, AutoGen, CrewAI), cloud platforms (AWS, Azure, GCP), and identity/access control patterns.

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 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.