AI Engineer

• AI Implementation - Design, build, and maintain all of our AI systems across the company. Everything from internal marketing, sales, finance, and operations systems to local AI systems in our engineering workflows, and the Chamber itself.
• AI Adoption - Educate, Train, Support, and Uplift everyone in the company with their AI adoption. Running office hours, making tutorials, providing resources, sourcing solutions, and more.
• AI Infrastructure - Architect and operate a scalable set of infrastructure that allows non-technical, and technical teams to use AI in a secure and productive manner.
• AI Systems & Agents - In conjunction with departments, design, build and maintain all AI systems and agents. This includes administering and managing our off the shelf AI systems like Claude, Viktor, Cursor, etc. It also includes our custom built Agents, Skills, Plugins, Tools, and more.
• AI Security - You are responsible for creating, maintaining, and enforcing all data, privacy, and security policies across our AI systems and Agents. Organization, Department, and Role based permissions and settings across all our products.
• Other Projects - As this is a technical role, you will also be asked to help build other internal systems like automations, micro apps, and more.

AI Solutions Lead

• Define and maintain enterprise architecture standards, reference patterns, and governance guardrails for AI-enabled solutions moving from pilot to production.
• Establish decision models for build, buy, or integrate choices; model and vendor selection; data access; security; and responsible AI adoption.
• Design scalable architecture patterns for AI-enabled workflows and agentic processes across data, APIs, identity, security, and cloud platforms.
• Test new AI models, LLMs, agent frameworks, and tools to inform enterprise adoption.
• Design proof-of-concepts, define success criteria, and guide solutions from pilot to production.
• Lead architecture reviews and communicate trade-offs, risks, and growth to partners.
• Partner with teams to translate needs into governed, implementation-ready solutions.
• Ensure teams through demos, workshops, and reusable templates to support safe AI adoption.

Principal Architect – Enterprise AI

• Build agentic workflows for decision-making in healthcare
• Design and ship AI systems for healthtech
• Raise the technical bar across the organization
• Support and close exceptional founders in health technology

Principal Applied AI Engineer

• As a Senior AI Engineer within Bristol Myers Squibb's AI Venture Studio team, you will be a hands-on individual contributor responsible for building secure cloud-hosted applications.
• Design APIs, services, infrastructure patterns, deployment pipelines, and semantic-layer evolution patterns for agent context engineering.
• Collaborate with frontend engineers to define clean API contracts, streaming response patterns, error handling, and service-level behaviors for AI-powered user experiences.
• Create and maintain CI/CD pipelines, environment configuration, automated tests, and release processes for cloud AI applications.
• Partner with AI Engineers, Data Engineers, Data Scientists, and product teams to solve complex delivery challenges.
• Continuously refine delivery priorities and deliver MVP transition activities by maturing AI capabilities.

Senior AI Engineer

• Leading cloud VM platform initiatives from architecture and systems design through implementation, testing, and deployment.
• Designing, building, and operating scalable services that support secure, isolated agent workloads.
• Developing automation for infrastructure provisioning, VM lifecycle management, application delivery, configuration, monitoring, and remediation.
• Collaborating with engineering teams across NVIDIA to translate business and AI workflow requirements into dependable platform capabilities.
• Improving the platform’s reliability, scalability, observability, performance, and operational efficiency.
• Continuously raising standards for code quality, testing, documentation, infrastructure security, and production readiness.

Senior Software Engineer, AI Agent Compute

• Define and evolve the standards, architecture patterns, and tooling choices that govern how engineers use AI across the codebase — including where to invest in codebase readiness (instrumentation, specification, evaluation) versus targeted rewrites.
• Own execution of the multi-milestone plan (readiness → validated → governed) applied to corgi and secondary repos, in partnership with squad leads — without being their manager.
• Decide what AI tooling, agent infrastructure, and evaluation pipelines the org needs, and build or oversee the build of the ones that don't exist yet.
• Set the policy and technical controls for where human-in-the-loop review is required versus where autonomous agent action (PR review, deployment) is safe — resolving the tension between adoption speed and security/quality risk.
• Write the guidance engineers actually use — AGENTS.md/CLAUDE.md conventions, review norms for AI-generated code, eval standards — and make sure it's adopted, not just published.

AI Architect

• Own and refine the overarching AI platform story, with special emphasis on context-first document management, AI and agentic automations, scalability, security, and extensibility.
• Define differentiated messaging and value propositions for platform capabilities across personas and industries.
• Define differentiated FedRAMP messaging and value propositions for platform capabilities across personas and industries while supporting related content programs.
• Ensure consistency and clarity of AI platform-level messaging across all marketing, enablement, and sales touchpoints.
• Lead platform feature releases, orchestrating cross-functional launch strategies for AI, cloud, and core platform enhancements.
• Partner with Product Management to influence roadmap decisions based on market opportunity, customer needs, and competitive insights.
• Drive content strategy for platform launches, including pitch decks, solution briefs, whitepapers, demos, customer stories, webpages, and sales tools.
• Own competitive and market intelligence for platform-level capabilities, especially in AI-driven information management and cloud content services.
• Identify market trends, customer pain points, and emerging competitors to guide product and GTM strategy.
• Deliver actionable insights to Sales, Product, and Executive teams.
• Partner with Sales Enablement to ensure clear understanding of platform capabilities, differentiation, and value drivers.
• Support customer-facing teams with platform-level messaging guides, battlecards, objection handling, and training content.
• Collaborate with cross-functional teams to position M-Files as an industry leader in AI-powered information management.
• Represent M-Files in webinars, events, analyst briefings, and customer engagements as a platform subject-matter expert.

Senior Product Marketing Manager, M-Files AI Platform, Cloud

• Improve operational efficiency, resilience, and process quality by establishing scalable AI automation architecture standards and governance guardrails
• Accelerate transformation delivery and reduce rework through clear design frameworks, decision models, and reusable automation patterns
• Enhance employee and customer experience by reducing manual work, process fragmentation, and automation risk
• Embed AI-first architectural practices that improve automation scale, decision quality, and measurable business outcomes
• Lead evaluation of AI automation, agentic workflow, and transformation initiatives across the organization
• Define architectural decision frameworks and long-term platform strategy for n8n, Boomi, APIs, event-driven orchestration, and AI services to reduce duplication and increase reuse
• Establish governance guardrails for AI-enabled workflows, agents, prompts, models, data flows, and human-in-the-loop controls to ensure scalability, reliability, auditability, and responsible use
• Anticipate growth, compliance, security, and operational risks across automation platforms and transformation programs before they materialize
• Influence cross-functional roadmaps with AI Automation Engineers, BSAs, and business leaders based on architectural trade-offs, platform fit, and measurable outcomes
• Translate enterprise capability needs into clear, implementable technical designs that accelerate AI automation delivery
• Create architectural blueprints for intelligent workflows, agentic process patterns, and cross-system orchestration that reduce ambiguity and minimize rework
• Design secure, scalable, and resilient automation patterns across SaaS systems, internal platforms, APIs, data ecosystems, and AI/ML services
• Drive API-first, event-driven, and human-in-the-loop architecture standards that improve interoperability, control, and long-term maintainability
• Lead architecture reviews and represent AI automation and transformation strategy in executive and cross-functional forums

Principal Enterprise AI Architect

• AI Configuration: Design, prompt, and configure custom AI Agents to seamlessly integrate into the claims process. This includes co-pilot for adjuster guidance, Photos & Documents analysis (data extraction, summarization, automation), and designing code-less AI Agent workflows.
• Architect and Build: Proactively develop the industry’s best operational flows, utilizing Snapsheet’s Claim Platform and the most advanced AI and automation tools, developing objective metrics to show impact and ROI, and help customers adopt these new processes across their organizations.
• Client Advisement: Serve in a strategic, account management style capacity, leading weekly client meetings to understand operational pain points, desired outcomes, and roadmap priorities.
• Technical Unblocking: Proactively unblock customer bottlenecks related to AI configurations, prompting techniques, and system parameters (e.g., model settings, context window data).
• Cross-Functional Liaison: Act as the primary conduit between the client, engineering, and support teams. Translate customer needs into actionable feature requests and serve as the first line of technical support for the engineering team.
• Consultative Strategy: Make expert recommendations on system configurations and AI utilization to drive value, automation, and efficiency for the customer's claims organization.
• Continuous Improvement: Provide internal feedback on existing AI features and actively contribute to the design and implementation of new capabilities.

Senior AI Implementation Engineer

• Partner with internal and external stakeholders to re-envision and scale Core Engineering technologies, including the design and build of a suite of AI Agents
• Drive technical excellence and governance of AI Agents as use-cases are identified across Snap Engineering
• Collaborate across teams to understand product requirements, evaluate architectural trade-offs, and deliver solutions needed to build innovative products and services
• Champion best practices in availability, scalability, operational excellence, and cost management
• Serve as a technical mentor to senior engineers and a thought partner to engineering leaders
• Contribute to the technical roadmap for AI Agents and Core SWE infrastructure, ensuring alignment with organizational goals
• Partner closely with Product, Finance, Sales, and Engineering teams distributed across multiple offices
• Influence key architectural and implementation decisions for scalable, reliable, and cost-effective engineering solutions
• Iterate quickly without compromising quality and continuously raise the bar on operational excellence
• Adapt technical plans nimbly in response to evolving customer and business needs

Staff Software Engineer, DevProd AI

• Collaborate with customers to develop agent capabilities and workflows
• Design, ship, and operate agentic systems for large-scale data
• Build dependable tools and interfaces
• Develop and maintain the MCP server
• Work across the entire stack

Software Engineer, Full Stack – Agentic AI

• Talk directly to customers and partner with product to turn real review workflows into agent capabilities: generating dashboards, writing analysis scripts, and surfacing insights buried in their telemetry
• Design, ship, and operate agentic systems that reason over large-scale time-series data and hardware domain context
• Build everything around the model that makes agents dependable: tool interfaces, sandboxed execution for agent-generated code, context and memory management, custom compaction algorithms, opinionated skills, and guardrails
• Develop and maintain Sift’s MCP server, the tool surface that lets both our agents and our customers’ AI tools query telemetry directly
• Work across the whole stack
• Build the frontend surfaces where Sift Agents live, and make them feel great
• Design and implement the APIs that power our agentic capabilities
• Run agents reliably at scale, both in the cloud and on-prem
• Build evaluation suites that measure whether agents actually help engineers, and instrument quality, latency, cost, and failure modes in production
• Integrate and assess frontier models across providers

• talk directly to customers and partner with product to turn real review workflows into agent capabilities
• design, ship, and operate agentic systems that reason over large-scale time-series data
• build everything around the model that makes agents dependable
• develop and maintain Sift’s MCP server
• work across the whole stack
• build the frontend surfaces where Sift Agents live
• design and implement the APIs that power our agentic capabilities
• run agents reliably at scale
• build evaluation suites that measure whether agents actually help engineers

Senior Software Engineer, Full Stack – Agentic AI

• Partner with business and technology teams to identify, evaluate, and prioritize AI use cases.
• Translate business needs into scalable AI solution designs and implementation plans.
• Lead delivery of AI-enabled products and solutions from concept through production.
• Provide technical leadership to engineers, contractors, and delivery teams.
• Guide architecture, design, and implementation decisions related to AI and software engineering.
• Present AI capabilities, demonstrations, and solution recommendations to business and technical stakeholders.
• Collaborate with enterprise AI, architecture, and technology organizations to align initiatives and leverage existing capabilities.
• Influence AI strategy, adoption, and best practices across WCIB.
• Support team growth through mentoring, leadership, and participation in hiring activities.

AI/ML Enablement Lead Engineer

• Build production AI platform capabilities that transform Prologis building, project, asset, and operational data into reusable solutions for construction, procurement, and operations teams.
• Design and implement production AI platform capabilities, including agents, retrieval-augmented generation, tool calling, workflow orchestration, evaluation, and human review.
• Build an AI-native building knowledge platform that links building models, assets, documents, telemetry, and operational context.
• Develop multimodal data pipelines that convert BIM, Autodesk, geospatial, document, and operational data into structured, queryable knowledge.
• Deliver AI workflows supporting design, construction, commissioning, building operations, sustainment, and reinvestment use cases.
• Move priority solutions from prototype through pilot and production with appropriate governance, documentation, evaluation, observability, and operational readiness.
• Establish reusable engineering patterns that enable successful pilots to scale into enterprise platform capabilities.
• Partner with business, technology, security, and operations teams to define workflows, technical scope, implementation plans, rollout approaches, and post-launch improvements.

Lead AI Engineer

• Lead technical and writing teams to deliver NEMO products.
• Act as the liaison between customers, DataFactory teams, product teams, and research teams.
• Track annotator metrics to ensure top-quality deliverables.
• Write creative prompts and responses across diverse topics.
• Manage labeling initiatives with third-party firms and internal customers.
• Develop and update detailed guidelines and specifications for stakeholders.
• Train teams on best practices for creating large language models and datasets.
• Handle potentially toxic or offensive content as required (e.g., sexually explicit, graphic, or disturbing material).

Lead Generative AI Analyst

• Architect and evolve the complete AI stack for Adobe Express
• Develop and operationalize end-to-end systems
• Develop large-scale data and inference infrastructure
• Develop high-performance runtime services for inference and orchestration
• Lead development of experimentation and evaluation systems
• Work closely with applied research, product, and platform teams
• Drive architectural strategy for Express AI Foundations
• Mentor senior engineers and scientists

Principal Architect, Express AI Foundations

• Architect, design and develop RESTful API Endpoints, ensuring high performance, scalability and maintainability.
• Collaborate closely with front-end engineers to build dynamic, responsive, and user-centric web applications that deliver seamless user experiences.
• Define robust data models and database schemas, and manage relational or NoSQL databases with a strong emphasis on data integrity and performance optimization.
• Direct and govern AI coding agents across the delivery lifecycle, setting context, reviewing agent-generated output, and enforcing SEPS delivery standards at every gate.
• Design and maintain agent workflows using agentic coding tools (Claude Code, Cursor, Copilot) and the AI-native development framework, ensuring structured, auditable, and high-quality delivery.
• Configure and maintain prompt engineering patterns, structured output schemas, with rules and guardrails to align agent behavior with SEPS platform standards.
• Trace, debug, and triage agent tool calls, prompt failures, and unexpected outputs, maintaining visibility into AI-assisted delivery at every stage.
• Create and maintain clear, comprehensive documentation for application architecture, design, configuration, and ongoing maintenance.
• Provide accurate task estimations and delivery timelines, contributing to effective sprint planning and execution.
• Participate in the on-call rotation, responding promptly to production issues and ensuring system stability and uptime.
• Mentor and support junior engineers, fostering a culture of AI-native ways of working, learning, and continuous improvement.

AI Engineer jobs in California

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AI Solutions Lead

Principal Architect – Enterprise AI

Principal Applied AI Engineer

Senior AI Engineer

Senior Software Engineer, AI Agent Compute

AI Architect

Senior Product Marketing Manager, M-Files AI Platform, Cloud

Principal Enterprise AI Architect

Senior AI Implementation Engineer

Staff Software Engineer, DevProd AI

Software Engineer, Full Stack – Agentic AI

Software Engineer, Full Stack – Agentic AI

Senior Software Engineer, Full Stack – Agentic AI

Senior Software Engineer, Full Stack – Agentic AI

AI/ML Enablement Lead Engineer

Staff Software Engineer, DevProd AI

Lead AI Engineer

Lead Generative AI Analyst

Principal Architect, Express AI Foundations

Staff Software Engineer, AI Native