Top AI Automation Jobs in San Francisco Bay Area, CA

Design and implement AI agents, plugins, automations, and enterprise integrations for HR Technology platforms. Lead requirements gathering, technical analysis, solution design, testing, documentation, deployment, security, and data integrity efforts across HR, IT, and business stakeholders. Integrate platforms including ServiceNow, Workday, and other enterprise applications while supporting the HR automation and AI roadmap.

Lead AI partnership strategy and execution to grow AI Frontier Labs alliances. Own alliance performance, co-sell pipeline, joint GTM and solution development, partner account mapping, enablement, marketing, and executive alignment to scale generative AI adoption and revenue.

Design and analyze rigorous messaging experiments using A/B testing and causal inference. Build measurement frameworks, data pipelines, dashboards, automated analyses, and scalable data solutions for messaging campaigns. Partner with CRM, Product, Algorithms, and Engineering teams to translate ambiguous business questions into actionable recommendations and experimentation standards. Support messaging strategy across channels, timing, content, targeting, and new business verticals.

Lead client engagements in insurance data, analytics, and AI: define roadmaps, run discovery sessions, design solutions, manage delivery and teams, develop proposals, and ensure DataOps, cloud (AWS), governance, and best practices across AI and analytics initiatives.

Build AI-powered workflows, agents, integrations, and internal tools that automate People Operations. Partner with People, Engineering, and IT to modernize onboarding and other employee processes, while implementing secure access controls, human oversight, escalation paths, and production-ready architectures. Prototype with users, iterate quickly, and measure improvements in efficiency, employee experience, and operational consistency.

The AI Deployment Engineer will build, deploy, and scale AI solutions while collaborating across departments to ensure successful implementation and support of operational workflows.

Leads AI presales strategy, customer advisory, technical solution architecture, and team development. Translates business needs into AI use cases, prototypes, business cases, roadmaps, and repeatable offerings. Partners with sales, engineering, consultants, and technology vendors to support complex pursuits, executive briefings, demonstrations, proofs of concept, and AI business growth. Promotes responsible AI governance, tracks pipeline performance, develops thought leadership, and remains hands-on in high-impact customer engagements.

Build AI-powered software automating hiring, finance, capital planning, contract analysis, and operational workflows. Develop production features using LLM APIs, MCP servers, and agentic frameworks; integrate enterprise systems; transform expert processes into structured data and generated work; and collaborate directly with finance, legal, recruiting, accounting, and delivery teams. The role emphasizes autonomy, rapid execution, product judgment, and forward deployment with business experts.

Identifies business opportunities for AI and automation, gathers and documents requirements, develops business cases, supports solution design and delivery, facilitates stakeholder collaboration, assists with testing and change management, and tracks project outcomes, reporting, and benefits realization.

Build and deploy agentic and generative AI systems that automate risk and compliance investigations. Own full-stack ML systems, including data integrations, prompt tuning, orchestration, evaluation, productionization, monitoring, and transformer-based modeling across transaction, graph, text, and profile data. Collaborate with product, engineering, platform, and operations teams while leading strategic roadmaps and delivering scalable production systems.

Build and deploy agentic and generative AI copilot and autopilot systems for risk and compliance automation. Own end-to-end ML systems, including data integrations, prompt tuning, orchestration, evaluation, productionization, monitoring, and transformer-based model development. Collaborate with product, engineering, platform, and operations teams to improve fraud detection and analyst productivity. Drive strategic roadmaps and cross-functional programs with significant business impact.

Leads company-wide AI adoption, operating the AI Center of Excellence, developing champions, running cross-functional AI sprints, delivering training, managing AI tools and budgets, and measuring workflow adoption, time savings, and financial impact. The role partners with Engineering to distribute shared AI skills, evaluates vendors, reports outcomes to executives, and publishes successful use cases across departments.

Opportunistic role for exceptional candidates to define their own mandate applying frontier AI to biomedical science. Work spans agent platform, science, infrastructure, product, and commercial tasks with end-to-end ownership. Must be highly autonomous, AI-native, collaborative, and able to work onsite in South San Francisco.

Lead and scale a Customer Engineering team supporting production AI workloads. Own operational health, customer escalations, and technical issue resolution. Partner with Product and Engineering to translate customer feedback into product improvements. Drive automation, diagnostics, documentation, and tooling to reduce recurring issues and improve customer outcomes.

Build and support AI agents, automated workflows, system integrations, and generative AI solutions using Azure AI, Copilot Studio, Power Automate, Tines, and supporting code. Collaborate with stakeholders to define requirements, test and deploy reliable automations, implement logging and security, troubleshoot production issues, document solutions, and measure business outcomes. Integrate platforms such as Teams and Salesforce through APIs, webhooks, and connectors while validating AI-generated outputs.

Build and operate AI-powered automation, CI/CD systems, distributed services, developer tools, validation platforms, and code-intelligence capabilities. Own significant systems from architecture through production, improve engineering workflows using measurable results, scale reliable automation and delivery platforms, and integrate capabilities through APIs and MCP. Establish operational practices, participate in on-call support, conduct technical reviews, mentor engineers, and lead cross-team delivery of dependable engineering platforms.

Design, build, and operate AI-powered automation, CI/CD systems, distributed services, developer tooling, and code-intelligence platforms. Own significant capabilities from architecture through production, improve engineering workflows using measurable evaluations, scale reliable automation and delivery systems, and operate secure multitenant services. Lead technical reviews, define reliability practices, integrate platforms through APIs and MCP, mentor engineers, and drive ambiguous technical problems to dependable production outcomes.

Leads enterprise AI and intelligent automation strategy, including Generative AI, machine learning, and RPA initiatives. Manages a multidisciplinary IT team, budgets, vendors, governance, project portfolios, and end-to-end solution delivery. Partners with business and technology leaders to identify automation opportunities, develop business cases, ensure compliance and security, and deliver scalable solutions with measurable business value. The role is hybrid in Camden, New Jersey, with 15% domestic and international travel.

Architect and build production agentic AI systems for customer support and compliance automation. Lead technical direction for distributed systems, APIs, orchestration frameworks, guardrails, and evaluation systems. Create reusable automation primitives, improve grounding and reliability, reduce hallucinations, and mentor engineers on LLM application design and production readiness. Collaborate cross-functionally to scale AI automation across Coinbase.

Design, develop, test, deploy, and maintain UiPath RPA solutions enhanced with agentic AI. Analyze business processes, gather requirements, document workflows, integrate systems, monitor automated processes, troubleshoot issues, and optimize solutions. Provide user training and support while collaborating with stakeholders and recommending AI and automation best practices.

Designs, builds, tests, and deploys AI-enabled automations and copilots for GTM and RevOps. Creates reusable agent templates, prompt libraries, and orchestration patterns; implements end-to-end API integrations; monitors performance; documents and hands off production solutions; and trains/coaches business teams on safe, responsible AI usage and prompting best practices.

Lead development of agentic AI systems that autonomously plan, execute, analyze, and optimize laboratory experiments. Build integrations with robotic platforms and analytical instruments, implement closed-loop learning, deploy reliable containerized services, and ensure experiment data supports downstream model training. Own the platform roadmap, reliability, adoption, and technical direction while managing and mentoring a team of scientist-engineers. Collaborate with chemists, biologists, automation engineers, NVIDIA, vendors, and senior R&D leadership.

Engineer agentic AI and automation integrations connecting planning systems with laboratory instruments, robotic platforms, ELN/LIMS, and data pipelines. Build multi-agent workflows with orchestration, state management, tool integration, error recovery, and human oversight. Deploy containerized services using Docker, Kubernetes, Argo, GitOps, and CI/CD. Collaborate with scientists, automation engineers, and NVIDIA researchers to transition prototypes into reliable autonomous experimentation systems for drug discovery.

Build and scale agentic AI systems that automate customer experience workflows across Slack and Salesforce. Analyze transcripts, detect SLA risks and escalations, provide self-service operational insights, and develop AI memory architecture. Partner with data, QA, workforce management, and customer advocacy teams to ensure system accuracy, reliability, trustworthy outputs, and measurable operational impact. Productize internal tools and design human escalation patterns for scalable deployment.

Build and operate an AI-driven global sourcing platform covering web crawling, data ingestion, normalization, entity resolution, product matching, provenance, and source monitoring. Integrate Zoho CRM and QuickBooks, apply LLMs with structured evaluation and human review, and identify automation opportunities across business departments. Lead pilots, train employees, measure impact, and scale the platform to hundreds of sources.