Artificial Intelligence Jobs in Berkeley, CA

Develop, test, deploy, and support AI-powered applications, automation solutions, and agent-based systems. Translate stakeholder workflows into scalable technical solutions using Python, C#/.NET, TypeScript, React, Azure AI services, APIs, and orchestration frameworks. Implement RAG, prompt engineering, and agent workflows; maintain testing, documentation, security, monitoring, and support standards. Collaborate with engineering, architecture, legal, security, data, and business teams while contributing to pilots, user adoption, and continuous improvement.

Develop and maintain prompts, responses, and datasets for large language models. Lead labeling initiatives with internal teams and third-party firms, create stakeholder guidelines, and train teams on LLM and dataset development best practices. The role requires native-level English, bilingual proficiency in an additional language, specialized domain knowledge, and a college degree or equivalent experience.

Serve as the technical sales and customer-facing expert for an AI platform. Responsibilities include conducting product demonstrations, supporting proofs of concept, advising on architecture and development, planning professional services projects, tuning retrieval and agentic pipelines, responding to RFPs, supporting customer adoption, and communicating product feedback internally. The role requires strong AI, cloud, on-premise, application development, storytelling, and enterprise customer engagement experience.

Reviews and scores robotics data episodes using standardized quality rubrics. Identifies failures, unsafe behavior, edge cases, and recurring quality trends; documents findings and provides actionable feedback. Collaborates with stakeholders and teleoperators to improve review workflows, standards, training, and documentation while meeting throughput and accuracy targets.

Lead architecture and technical strategy for AI-driven product quality systems using LLMs and agents. Build scalable evaluation frameworks, detect regressions, generate insights, and drive cross-functional adoption while mentoring engineers and defining standards for trustworthy AI.

Drives new business acquisition and expansion of international shipping services through prospecting, strategic account planning, solution-based selling, presentations, negotiation, and closing. Collaborates with internal sales, brokerage, pricing, marketing, and customer success teams. Analyzes market trends, customer needs, financial indicators, and shipping activity while supporting customs compliance and visiting customer distribution facilities.

Partners with AI labs to integrate models, run evaluations, deliver results, and manage customer relationships. Builds pragmatic full-stack solutions, automations, onboarding workflows, and delivery tooling for cutting-edge AI teams. Translates customer and research feedback into product and engineering initiatives, supports strategic account growth, and serves as a technical point of contact across onboarding, releases, and issue resolution.

Own the strategy, architecture, evaluation, and production delivery of Jerry.ai’s AI agents and workflow automation platform. Lead chatbot, voicebot, computer-use agent, document validation, transaction orchestration, and external system automation initiatives. Evaluate emerging AI technologies, make technical investment decisions, partner with OpenAI, and collaborate closely with engineering and prompt engineering teams. The role requires hands-on experience launching LLM systems and managing evaluations, regressions, latency, cost, and failure handling.

Own the strategy, architecture, evaluation, and production deployment of Jerry.ai’s next-generation AI agents and workflow automation platform. Lead conversational agents, voicebots, computer-use agents, document validation, transaction orchestration, and external insurance-system integrations. Evaluate emerging AI technologies, make technical investment decisions, partner with engineering and OpenAI, and ensure systems meet requirements for reliability, latency, cost, regression prevention, and failure handling.

Leads complex government AI deployments from pre-sale discovery through production adoption, overseeing client relationships, delivery planning, cross-functional execution, change management, and executive communication. Translates agency workflows into technical requirements, manages risks and dependencies, drives measurable outcomes, and converts deployment feedback into product improvements. Builds deployment playbooks, operating cadences, and future delivery teams while supporting renewals and expansions. Requires strong AI/ML and enterprise systems fluency, senior stakeholder leadership, and 30–50% travel.

Build the enterprise platform for an AI creative product, including workspaces, permissions, SSO, audit logs, usage-based billing, invoicing, payment integrations, and security foundations. Develop backend services, APIs, and polished React/Next.js administrative interfaces for multi-tenant customers. Collaborate with founders, sales, and customers to define and ship enterprise features while taking increasing ownership of platform surfaces.

Build the enterprise platform for an AI creative product, including workspaces, roles, permissions, SSO, audit logging, usage-based billing, invoicing, and payment infrastructure. Design scalable APIs and multi-tenant architectures, strengthen security and reliability, and create React/Next.js administrative experiences. Partner with founders, sales, and customers to deliver enterprise requirements, establish engineering practices, and help shape the enterprise engineering team.

Lead the Agentic AI Lab’s full-cycle research agenda, including model and training design, data, evaluation, benchmarking, deployment, and publication. Train specialized enterprise models, define rigorous evaluation gates, move research from public benchmarks to customer shadow deployments, and build a small multidisciplinary team. The role partners closely with founders and platform engineers while establishing research direction, documenting technical decisions, and mentoring engineers into researchers.

Build, integrate, deploy, and operationalize secure AI solutions across enterprise platforms. Responsibilities include prompt engineering, orchestration, RAG implementation, enterprise data integration, monitoring, performance tuning, documentation, and governance compliance. The role partners with IT, Security, Privacy, Data, and business teams to deliver production-ready AI capabilities using technologies such as OpenAI, Anthropic, Microsoft 365, Salesforce, and ServiceNow.

Own the vision, roadmap, and delivery of e.l.f.'s agentic commerce capabilities across AI assistants, generative search, discovery, personalization, offers, and checkout. Partner with AEO/GEO, Connected Commerce, CRM, engineering, data science, design, and analytics teams to improve product visibility, citations, and conversion. Define requirements, run experiments, measure outcomes, manage risks, and establish agent-friendly commerce experiences and integrations.

Leads AI and legal technology enablement across West Coast law firm offices. Designs training curricula, academies, workshops, communications, and adoption campaigns; manages change initiatives; builds attorney stakeholder relationships; analyzes usage data; reports progress and risks; and promotes responsible, habitual technology adoption among attorneys and practice groups.

Lead cross-functional teams to design and deliver commercial analytics projects for life sciences clients. Provide strategic guidance, analyze data, develop actionable insights, manage client communications and timelines, build/optimize data processes (including coding and visualization), support business development, and mentor junior staff.

Lead development of next-generation AI systems for insurance automation, including document validation, voicebots, computer-use agents, and complex workflow orchestration. Set chatbot architecture and technical standards, build and deploy production automations, evaluate emerging AI technologies, and partner with OpenAI on voice models. Own LLM system reliability, including evaluations, regression prevention, latency, cost, and failure handling.

Build and lead next-generation AI systems for automated insurance quoting, customer support, document validation, voice interactions, and external system navigation. Set technical direction for chatbot architecture, evaluate emerging AI technologies, and deploy production LLM systems. Own automation outcomes end to end, including evaluation, regression prevention, latency, cost, and failure handling, while partnering with OpenAI on voice models and workflow automation.

Provide expert legal and business research to attorneys and staff using advanced research tools; advise on research strategy; manage research workflow; develop training, onboarding, newsletters, and intranet content; evaluate and recommend online resources; support continuous learning and Research Services initiatives.

Translate enterprise AI engineering work into compelling videos, articles, demos, and social content. Build marketing automation tools such as scrapers, agentic case-study generators, microsites, and pipeline dashboards using Python or TypeScript. Own publishing and measurement across major channels, run marketing experiments with real budgets, and connect storytelling to business results. The role requires strong writing, hands-on coding, genuine AI expertise, a portfolio demonstrating range, and willingness to work in New York or San Francisco.

Leads technical and writing teams delivering generative AI products, coordinating customers, data, product, and research teams. Tracks annotator metrics, manages labeling initiatives, creates prompts and responses, develops stakeholder guidelines, and trains teams on LLM and dataset best practices. The role includes customer interaction, quality assurance, and exposure to potentially toxic or sensitive content.

Own the AI roadmap for Operations, Finance, and HR systems, identifying and prioritizing automation opportunities across supply chain, inventory, accounting, and people processes. Translate business needs into product requirements, lead pilots and delivery, drive adoption, measure ROI, and communicate outcomes to executives. Partner with engineering, data science, IT, security, and vendors while ensuring AI governance, privacy, compliance, and operational reliability.

Lead US TMT business development with an AI focus: identify revenue opportunities from AI regulation, M&A, governance and data trends; develop client strategies, communications and targeted outreach; support pitches and major US TMT projects; coach and manage MBD colleagues; collaborate with partners and international teams to drive client relationships and revenue growth.

Design, build, and scale AI engines, conversational assistants, context-aware agents, and workflow automations for go-to-market teams. Own the GTM AI roadmap, trusted data and knowledge architecture, AI governance, production monitoring, adoption, and value realization. Partner with Sales, Marketing, Revenue Operations, Product, and Systems leaders to translate business needs into scalable AI solutions and measure their impact.