responsible-ai jobs in San Diego

As L3 production support lead for ClaimBeacon, a Guidewire-integrated agentic AI platform, you'll own end-to-end troubleshooting and resolution of production bugs, data pipeline failures, AI agent issues, and small enhancements across the full stack (Java, Python, Flutter). You'll reproduce issues using logs and monitoring tools, decide what escalates to core engineering, and ensure fixes maintain data/AI governance and compliance standards.…See more The role requires 5+ years of software engineering or production support experience with proven end-to-end ownership of production issues, plus comfort working across frontend, backend, data, and infrastructure in a live, high-pressure environment.

This is a hands-on Solution Architect role for an AI-enabled Managed Services team, requiring deep technical expertise in designing end-to-end application architectures spanning UI, APIs, services, data, and AI components. The role combines hands-on coding and prototyping with architecture ownership, emphasizing active participation in codebases, AI tool evaluation, and guiding engineering teams through complex technical decisions.…See more Key responsibilities include designing reference architectures for AI patterns (RAG, vector search, prompt orchestration), defining non-functional requirements (performance, reliability, security), architecting CI/CD pipelines, and ensuring production readiness. The ideal candidate has 8+ years of software engineering experience, strong cloud-native and modern application architecture knowledge, practical AI feature development, and comfort working directly in code and infrastructure.

Senior AI/ML Engineer responsible for shipping end-to-end production ML systems that enable autonomous medical coding in a SaaS platform. Will design robust ML architectures with low-latency inference, build reliable data and model pipelines using modern MLOps practices (CI/CD, model registries, experiment tracking), establish evaluation strategies with statistical rigor, and implement model observability and governance including drift detection and bias assessments.…See more Requires 5+ years of industry experience building and operating ML systems in production, 3+ years with C# or Python, 3+ years on Azure, and 1+ years of LLMOps expertise including prompt engineering and RAG.

The AI Learning Architect designs and implements generative AI applications for learning and development, using prompt engineering, retrieval-augmented generation, and low-code automation to personalize training content and remove manual steps. They structure learning data into modular frameworks, evaluate and integrate AI tools with existing learning platforms, set up analytics tracking via xAPI, and debug prompt configurations to keep solutions accurate and current.…See more The role requires 3+ years in instructional design or educational technology with hands-on AI integration, proficiency in modern generative AI models and low-code tools, knowledge of learning frameworks (ADDIE, SAM), and the ability to translate technical AI behavior into accessible user experiences. They embed responsible AI practices including data privacy, bias checks, and accessibility from the start, while documenting workflows and coaching teammates.

Senior technical leader responsible for integrating AI/ML systems into secure, scalable DoD-compliant environments. Will architect AI system deployments, establish DevSecOps practices, ensure compliance with RMF/NIST 800-53/DISA STIG standards, and provide technical guidance across engineering teams.…See more Requires deep expertise in AI/ML production systems, containerization, CI/CD, and cybersecurity controls, with hands-on experience in Python, Kubernetes, and modern infrastructure tooling.

Lead enterprise AI platform strategy and execution at a biotech company, driving end-to-end program delivery across engineering, data, cybersecurity, and product teams. Own platform health, KPIs, and telemetry; establish governance, safety guardrails, and regulatory compliance for AI-enabled solutions in a regulated environment.…See more Define multi-year AI roadmaps, coordinate cross-functional dependencies, and orchestrate Agile delivery while partnering with legal, compliance, and tech enablement to ensure scalability, security, and enterprise adoption.

Staff Quality Analyst role responsible for building dashboards and analytics that surface defect signals and drive leadership decision-making at scale. The role combines hands-on data analysis (SQL, Python, statistics) with AI-native workflows to accelerate defect detection and root cause analysis, plus structured change management to land measurement and process changes across large stakeholder groups.…See more Required skills include strong SQL/Python proficiency, applied statistics, experience with defect frameworks (DPMO), contact center operations familiarity, and demonstrated ability to communicate data findings credibly to executives and manage organizational change.

This role combines prompt engineering expertise with AI system governance and enterprise adoption strategy. The engineer will optimize LLM performance across platforms (OpenAI, Anthropic), design and configure AI agents and chatbots with knowledge grounding, and establish prompt governance frameworks and best practices.…See more Success requires 5+ years in AI/ML systems, 2+ years of hands-on prompt engineering, and demonstrated ability to evaluate AI performance, manage knowledge systems, and guide enterprise clients through AI tool adoption and deployment.

AI Architect role requires designing and delivering enterprise-scale AI/ML solutions on AWS, with 5–7 years of cloud experience and 2–3 years hands-on with LLMs, agentic frameworks, and AI/ML services. The position demands deep expertise in AWS AI services (Bedrock, SageMaker, Kendra), orchestration frameworks (LangChain, LangGraph), RAG pipelines, MLOps tooling, and responsible AI principles.…See more Candidates must architect scalable, cost-optimized solutions integrating AI with cloud infrastructure, data platforms, and microservices, and communicate complex technical concepts to executive and technical audiences.

Lead Qualcomm's GenAI transformation for embedded and software engineering, building reusable AI agents, agentic workflows, and developer productivity tools that scale across teams. Partner with platform and engineering teams to establish secure AI practices, governance models, and metrics while serving as a technical thought leader who shapes the organization's transition to AI-native engineering workflows.…See more Requires Principal-level technical leadership with deep expertise in generative AI, LLM-based systems, and hands-on experience deploying GenAI solutions in complex engineering environments. Collaborate on code generation, code review, test automation, and release readiness use cases while driving measurable productivity and quality improvements.

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.

Staff engineer leading architecture and evolution of Qualcomm's Ambient Perception Platform for always-on, context-aware AI on power-constrained edge devices. Responsibilities include designing low-power AI runtime platforms, multimodal sensing systems, secure data architectures, and heterogeneous computing frameworks across Android, Linux, Windows, XR, automotive, and IoT.…See more Requires 4+ years software engineering experience (or equivalent with advanced degree), 2+ years with C, C++, Java, or Python, and expertise in embedded systems, ARM/DSP/NPU optimization, and edge AI workload efficiency. Strong preference for 8–12+ years in software architecture, platform frameworks, and heterogeneous SoC development.

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.

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.

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.

Lead end-to-end product management for advisor-facing AI experiences within LPL Financial's AI Business Solutions team. Own product vision, roadmap, and delivery lifecycle from opportunity framing through commercialization and scaled adoption.…See more Define advisor chat and agentic AI capabilities, evaluate third-party AI vendors, and ensure measurable business impact aligned to enterprise OKRs. Collaborate in a four-in-a-box model with Technology, Business, and Operations & Risk to co-design product definitions, data contracts, evaluation frameworks, and governance documentation.