Top AI Automation Jobs in San Francisco Bay Area, CA

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.

Build end-to-end internal AI agents and workflow automations: discover high-value opportunities, redesign processes, implement LLM-based agents with integrations, deploy and operate solutions, and ensure security, compliance, monitoring, and adoption across GTM teams.

Hands-on technical leader who designs, builds, and deploys production-grade AI automation and agentic workflows. Responsibilities include rapid prototyping, RAG and document-intelligence systems, API integrations, orchestration, monitoring, reusable AI assets, and mentoring a small engineering team to deliver frequent releases and measurable business impact.

Own and administer Salesforce and NetSuite while designing and deploying production-grade AI-driven automations and agent workflows. Ensure data governance, PHI/HIPAA compliance, release management, and quote-to-cash integrity. Partner cross-functionally to prioritize work, coach teams, document systems, and measure impact of automation on operations and revenue.

Build and ship AI-native systems for a fintech app: AI agents, RAG/retrieval systems, tool-calling and automation for onboarding, KYC, support, risk, CRM and operations. Work with product and engineering to design reliable, low-hallucination, cost- and latency-aware solutions and turn manual processes into scalable AI-enabled systems.

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.

The SME will develop a curriculum on AI for finance, creating engaging content and videos to train finance professionals in AI applications. They must leverage their extensive finance experience and AI understanding to enhance learner success.

Founding developer relations role owning developer discovery, docs, tutorials, runnable examples, community (Discord), events, and AI-powered content automation. Write deep technical posts, keep docs current, run community engagement, measure content impact, and feed product learnings back to engineering. Hands-on builder who reads code, ships examples, and scales DevRel systems.

Build and deploy production micro-apps and LLM-powered agents on a governed GCP platform. Integrate AI with systems (Salesforce, Slack, NetSuite, SQL), harden apps with auth, secrets, CI/CD, logging and monitoring, automate maintenance, and implement evaluation and observability for model quality and drift.

Contribute to building and hardening micro-apps and AI integrations on a shared GCP platform. Complete bug fixes and small features, participate in code and design reviews, apply security and software development best practices, monitor applications and follow runbooks, and use AI tools to assist development, testing, and documentation while learning from senior engineers.

Design and deliver LLM-powered, agentic AI systems to automate customer support and compliance. Build scalable, secure backend infrastructure in Python and Go, integrate third-party models/APIs, implement grounding and guardrails, and measure performance. Lead end-to-end projects, mentor engineers, conduct code reviews, and participate in on-call and incident response to improve resolution times and reduce operational costs.

Lead intake, roadmap, and governance for an AI automation/platform team. Harden and ship business-built AI apps to production with secure GCP platforms, define acceptance criteria and responsible-AI gates, manage vendor buy-vs-build decisions, drive adoption, measure outcomes, and manage AI economics and stakeholder communication.

Support AI project teams by executing workstreams, preparing client-facing presentations and documentation, assisting implementation activities, maintaining required certifications, using relevant technology, communicating with stakeholders, and traveling as needed for client engagements.

Build scalable QC systems and validation pipelines for RL training data: define quality standards, design metrics and experiments, audit supplier datasets, partner with vendors to diagnose failures, and integrate learnings into infrastructure and vendor tooling.

Lead design, prototyping, deployment, and continuous improvement of AI-powered applications, agents, copilots, and automations. Integrate AI with portals, workflows, data platforms, and AWS; define reusable patterns (RAG, prompts, agent workflows); ensure secure, observable, and cost-effective production systems; measure adoption and ROI; and mentor engineers, contractors, and vendors.

Lead development and scaling of a customer-facing AI agents platform. Own roadmap, prompt strategies, evaluation frameworks, and guardrails. Partner with engineering and OpenAI to deploy voice and automation models, improve automation rates and answer quality, and drive experiments using data and SQL.

Lead product development and scaling of Jerry.ai's AI agent platform. Define roadmap, design prompt strategies and guardrails, partner with engineering and OpenAI, run experiments to improve automation, answer quality, and customer satisfaction, and establish platform standards and evaluation frameworks.

Lead development and scaling of an agentic AI platform that automates customer sales and service using LLMs, human-in-the-loop feedback, and APIs. Drive roadmap, prompt strategies, evaluation frameworks, guardrails, and partnerships (e.g., OpenAI) to improve automation rates, quality, and customer satisfaction.

Lead development and scaling of a customer-facing AI agent platform: design prompt strategies, evaluation frameworks, guardrails, and integrations with OpenAI. Partner with engineering to improve automation, answer quality, and customer satisfaction through experimentation and production-grade deployment of LLM-based agents and workflow automation.

Lead end-to-end development and scaling of a customer-facing AI agents platform using LLMs and internal APIs. Define prompt strategies, evaluation frameworks, guardrails, and experimentation to improve automation rates and customer satisfaction while partnering with engineering and OpenAI.

Lead product development and roadmap for an agentic AI platform that automates customer sales and service. Partner with engineers on prompt strategies, evaluation frameworks, guardrails, and API/system design. Drive experimentation to improve answer quality, automation rates, and customer satisfaction, and work with partners like OpenAI to deploy advanced voice and workflow models.

Partner with functional SMEs to map and redesign processes using AI-first solutions. Prototype and build agentic workflows and integrations (Box, Workday, Salesforce, NetSuite, BigQuery), own data pipelines, apply security/compliance controls, operate production systems, and evangelize AI automation across teams.

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.

Lead design and implementation of AI-first testing frameworks and automation to validate LLM integrations and agentic Product Led Growth workflows. Perform white-box testing, identify and fix quality gaps, implement human-in-the-loop model evaluation, and collaborate cross-functionally to integrate quality across the agile delivery lifecycle.