multi-agent-systems jobs in San Diego

Design, build, and deploy production agentic AI solutions powered by Claude for enterprise clients, from proof-of-concept through production. Implement multi-agent systems that automate business processes, integrate with enterprise tools, and operate within defined autonomy and guardrails.…See more Modernize existing AI/ML platforms with generative AI capabilities including RAG and agent-based orchestration. Advise clients on generative AI adoption strategy, responsible AI practices, and model selection while partnering with technology, data, and business stakeholders to scope and deliver solutions.

Lead enterprise generative AI architecture and solution design on Oracle Cloud Infrastructure (OCI), focusing on agentic workflows, retrieval-augmented generation pipelines, and Oracle application integrations. Define governance, security, and compliance standards for AI/ML initiatives across the enterprise.…See more Mentor delivery teams on prompt engineering, model selection, and optimization; identify high-value AI use cases and guide pilot deployments that drive business outcomes.

Senior Staff Software Engineer responsible for architecting and leading Intuit's Virtual Expert Platform (VEP), an agentic AI customer success system that serves Customer Success Managers, onboarding specialists, and partner teams. The role requires deep hands-on development (50–70%) alongside strategic architecture work, designing multi-agent systems end-to-end, establishing technical standards and AI safety frameworks, and driving complex cross-team technical problems to resolution.…See more This engineer will define observability and guardrail patterns for AI in production, mentor senior engineers, and influence product roadmap strategy with senior business leaders.

Lead a small engineering team responsible for integrating autonomous flight control systems, payloads, and embedded hardware across complex autonomy stacks. Own interface contracts with C2 providers, drive standards compliance (UCI, OMS, MOSA, WOSA, TAK/CoT), and support live mission operations, test exercises, and customer demonstrations with hands-on debugging and field troubleshooting.…See more Require 7+ years of systems/autonomy experience plus 2+ years of direct people management; build and mentor engineers while driving continuous improvement in integration timelines and deployment reliability.

Sr. Engineer responsible for designing, building, and deploying production-grade AI platforms and solutions centered on LLMs, RAG, and agentic workflows.…See more The role spans full-stack development—from backend services and APIs to cloud-native infrastructure on Kubernetes—with emphasis on enterprise search, retrieval optimization, and AI application integration. Must have strong programming skills across Python, Java, C#/.NET, Rust, TypeScript/JavaScript, and proven experience architecting and operating scalable, production-ready AI systems.

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 Software Engineer role focused on building autonomous trajectory planning and motion control software for single and multi-agent systems. The engineer will develop reliable, maintainable C++ software with Python for prototyping and testing, diagnose complex algorithmic and software failures, and take features from ideation through flight testing.…See more Requires a Master's degree in computer science or robotics (or PhD) with 5+ years of professional experience building and debugging motion planning, robotics, or autonomous systems software. The role includes mentoring junior engineers and collaborating across teams to refine requirements and deliver scalable autonomy architectures.

As a Forward Deployed Engineer IV in Applied AI at Google Cloud, you will lead end-to-end engineering for production conversational AI systems, transforming prototypes into scalable agentic workflows deployed at customer sites. You'll architect multi-agent systems using frameworks like ReAct, optimize RAG implementations, debug agent logic across microservices, and connect AI systems to enterprise infrastructure.…See more The role requires 8+ years of software development (Python or similar), experience with infrastructure-as-code (Terraform), cloud platform deployment (GCP), and hands-on full-stack application development. You'll travel up to 50% and work directly with customers to establish production AI journeys while identifying patterns that feed back into product improvements.

This role leads enterprise generative AI architecture and solution delivery on Oracle Cloud Infrastructure, designing agentic workflows, RAG pipelines, and LLM-based integrations with Oracle applications. The candidate will define AI governance and security standards, identify high-value use cases, mentor technical teams, and guide model selection and optimization.…See more Requirements include 8+ years of enterprise architecture experience with 2+ years in AI/ML/GenAI solution architecture, hands-on expertise with OCI services (Generative AI Service, Functions, API Gateway, Data Science, Autonomous Database, Integration Cloud), and proficiency in Python, SQL, and REST APIs.

Build and integrate agentic AI systems with physical laboratory automation platforms (Hamilton, Tecan, Opentrons) and LIMS infrastructure to autonomously design, run, and refine chemistry and biology experiments. Design multi-agent orchestration architectures with state management, error recovery, and tool integration; prototype agent planning strategies and memory systems; deploy containerized services on Kubernetes with GitOps and CI/CD.…See more Work hands-on with chemists, biologists, and automation engineers to transition prototypes into production lab operations that measurably accelerate the Design-Make-Test-Analyze cycle.

Lead the design, development, and deployment of enterprise-scale Generative AI and LLM solutions across Azure and AWS environments. Define AI architecture frameworks, standards, and governance practices while architecting RAG systems, agentic AI, multi-agent systems, and vector database solutions.…See more Partner with business leaders and engineering teams to translate business requirements into scalable, secure, and responsible AI platforms. Mentor architects and data science teams while evaluating emerging AI technologies and driving innovation initiatives.

Lead research projects in AI/ML across areas including decision-focused AI, probabilistic modeling, causal inference, agentic systems, neuro-symbolic AI, and LLM-based reasoning. Define technical direction, mentor junior researchers, and translate research innovations into Intuit's products.…See more Requires a PhD, 8+ years of post-PhD research experience with top-tier publications, and deep expertise in one or more focus areas. Proficiency in Python, PyTorch, or TensorFlow, and strong fundamentals in deep learning, optimization, and statistical machine learning are essential.

Zensar is seeking an experienced AI Architect to design, develop, and deploy enterprise-scale AI and Generative AI solutions. The role requires deep expertise in Large Language Models (Claude, Gemini, OpenAI), multi-cloud platforms (Azure, AWS), and enterprise architecture, with 10+ years in software/cloud architecture and 5+ years designing AI/ML solutions.…See more Responsibilities include defining AI strategy and architecture standards, designing end-to-end GenAI systems (RAG, agentic AI, multi-agent systems), architecting secure infrastructure across Azure and AWS, establishing governance and responsible AI frameworks, and leading adoption programs. The ideal candidate will mentor teams, evaluate emerging technologies, and translate business requirements into scalable, production-grade AI systems.

The AI Architect II is a senior technical leadership role responsible for establishing architectural standards and patterns for AI solutions, including RAG pipelines, agentic workflows, and model serving. The role involves designing scalable AWS cloud architectures, defining MLOps practices, implementing responsible AI governance, and translating business requirements into enterprise AI and cloud strategies.…See more The position requires hands-on technical expertise to evaluate and integrate AI/ML services, lead systems design across microservices and event-driven architectures, and mentor engineering teams on cloud and AI best practices. This role drives technology decisions with real business impact while modernizing the company's platform through cloud-native and AI transformation initiatives.

The AI Architect will lead the design, development, and deployment of enterprise-scale generative AI solutions across Azure and AWS, partnering with business and engineering leaders to define AI strategy and architecture standards. The role requires deep expertise in modern LLMs (Claude, Gemini, OpenAI), multi-cloud AI platforms, and enterprise architecture, with 10+ years in software/cloud architecture and 5+ years architecting AI/ML solutions.…See more Key responsibilities include designing end-to-end GenAI solutions leveraging RAG, agentic AI, and multi-agent systems; establishing cloud-native deployment patterns; and defining governance, compliance, and responsible AI frameworks. The ideal candidate will serve as a trusted technical advisor to executives, mentor engineering teams, and drive AI adoption through reusable frameworks and reference architectures.

Staff engineer role focused on integrating autonomy software across Shield AI's Hivemind platform, spanning simulation, hardware-in-the-loop, and flight systems. Responsibilities include developing deep expertise in the autonomy stack, configuring and deploying multi-agent systems, integrating new autonomy capabilities, enabling platform bring-up on new robotic hardware, architecting integration tooling and deployment infrastructure, ensuring cross-platform compatibility, diagnosing integration defects via telemetry analysis, and optimizing CI/CD workflows.…See more The role bridges engineering development and real-world autonomous applications, requiring systems integration expertise, robotics platform knowledge, and hands-on proficiency with sensor drivers, middleware, and deployment frameworks.

Lead technical delivery of complex autonomy capabilities for Shield AI's V-BAT and X-BAT unmanned aircraft platforms, spanning mission autonomy, payload integration, flight-control interfaces, and multi-agent behaviors. Own end-to-end integration from architecture through field deployment, coordinate across Aircraft, Autonomy Capabilities, Perception, and GCS teams, and drive mission readiness for customer releases.…See more Mentor engineers, improve engineering practices, and serve as primary technical partner to the Aircraft team on integration approaches and interface design. Requires 7+ years of relevant experience, expert C++ and Linux development, and deep expertise in complex autonomy systems or embedded systems integration.

This intermediate-level role develops AI-enhanced decision systems for government sponsors, applying machine learning, large language models, and decision science to mission-critical problems. You will design, prototype, and evaluate AI solutions in cross-functional teams, lead R&D initiatives, and work hands-on with modern AI techniques including deep learning, reinforcement learning, generative AI, and multi-agent systems.…See more The role requires 2+ years of hands-on ML experience (or 1 year with a Master's degree) and proficiency in Python and/or C++, with the ability to communicate complex technical concepts to both technical and non-technical audiences.

As a Mission Software Engineer, you will own software solutions deployed to autonomous systems customers, developing capabilities across networking, autonomy, systems integration, and robotics. You'll troubleshoot live deployments, create performance metrics for debugging, and collaborate with multidisciplinary teams and end-users to translate operational needs into mission-ready features.…See more The role requires 3+ years of C++, Python, or Rust experience in Linux environments, with a strong engineering background and ability to navigate complex codebases quickly. You must be a U.S. citizen eligible for security clearance and based in or willing to relocate to San Diego.

Senior Applied AI Engineer at West Health will design, build, and deploy production-quality AI-powered tools and workflows using large language models, multi-agent architectures, and orchestration platforms. The role involves building intelligent automation pipelines with tools like n8n, LangChain/LangGraph, and Microsoft Copilot Studio, integrating AI capabilities with existing data infrastructure (Snowflake, Python), and conducting data analysis to identify high-impact AI opportunities.…See more The ideal candidate combines deep practical expertise in applied AI with the ability to rapidly move from concept to fully working, well-documented applications that create measurable value for healthcare delivery and senior care initiatives.