Artificial Intelligence Jobs in Fremont, CA

Own growth marketing for an AI systems integrator by translating engineering work into compelling stories, videos, demos, and written content. Manage and measure channels including LinkedIn, YouTube, and X; run experiments against pipeline outcomes; and build lightweight tools, dashboards, scrapers, and microsites. The role requires strong writing, genuine AI interest, working-level Python or TypeScript skills, and comfort using AI coding tools. Candidates may be early-career and must be in New York or San Francisco or willing to relocate.

Own the end-to-end product management cycle, including customer discovery, user interviews, solution definition, product requirements, AI prototyping, engineering collaboration, feature launches, and communicating product value. The role focuses on rapidly delivering mobile and web products that improve construction workflows, using data and decisive ownership to address complex customer and operational needs.

Develop and manage AI and ISV partner business development initiatives for Nebius’s AI cloud platform. The role involves collaborating with partners, managing strategic relationships, and supporting growth across AI infrastructure and cloud services. The posting provides limited specific responsibilities or qualifications, but emphasizes English proficiency and authorization to work in the country of application.

Own the financial services product line from discovery through launch and iteration. Set the roadmap, determine which deployment capabilities become core product features, conduct user discovery, define quality standards, and establish accuracy, human-review, citation, and safe-failure models for regulated workflows. Prototype in design or code, collaborate with engineers and designers, understand the market, and deliver reusable AI capabilities across financial institutions.

Develop and support AI-powered applications, automation solutions, and agent-based systems for business operations. Responsibilities include software development, integrations, Azure AI configuration, RAG and prompt engineering, testing, architecture participation, monitoring, troubleshooting, documentation, security collaboration, code reviews, and user enablement. The role works cross-functionally with engineers, stakeholders, legal teams, data professionals, and technology partners to deliver scalable and reliable AI solutions.

Design and build scalable AI platform capabilities to enable multi-step GenAI workflows, model execution, and integrations. Implement backend services, execution infrastructure, APIs, and observability to support production GenAI experiences across sales and product teams. Collaborate with AI engineers, data scientists, and product partners to turn AI use cases into reliable, extensible platform features.

Own strategic territories and close net-new enterprise software deals. Lead value-based sales cycles from discovery through proof of value, negotiation, and close; build executive relationships; develop account strategies; maintain Salesforce pipeline and forecasts; partner with alliances teams; and advise customers on supply chain resilience, risk, and compliance.

Supports the GTM Lead and founders across sales, growth, and content. Responsibilities include creating technical content for AI products, running growth experiments, supporting outbound initiatives, building the sales funnel, communicating with technical buyers, and collaborating with engineering in an early-stage environment.

Build Lingopal’s go-to-market motion for its evolving AI agent platform. Develop positioning, target accounts, outbound strategy, sales processes, and pricing inputs. Own enterprise sales from prospecting through discovery, pilots, and closing across customer-support-heavy enterprises and scaling AI-agent companies. Engage senior buyers including Chief AI Officers, COOs, and CTOs, while feeding market insights back into product strategy.

Build Weave’s AI-native lead generation infrastructure from scratch, including agentic workflows, automation, lead sourcing, enrichment, qualification, targeting models, and multichannel campaigns. Partner with account executives and RevOps to define lead quality, maintain HubSpot data hygiene, improve handoffs, and connect lead quality to pipeline conversion. Run data-driven experiments to optimize engagement, conversion rates, and pipeline contribution.

Architect, build, deploy, and operate production-grade AI agentic systems and workflows. Responsibilities include backend and full-stack development, agent orchestration, workflow state, retrieval, memory, approvals, failure recovery, data architecture, enterprise integrations, cloud infrastructure, observability, security, and scaling. The role establishes reusable engineering patterns and partners with users to deliver reliable AI products, while addressing production issues involving model behavior, permissions, latency, cost, and consistency.

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.

Develop and execute growth marketing for enterprise AI systems by translating technical work into compelling stories, videos, demos, and case studies. Shape company positioning, own social and content channels, build marketing tools and agentic workflows, track pipeline impact, and run experiments. The role combines strategic marketing, business storytelling, content creation, coding, and AI research.

Develop and execute go-to-market strategy for AI products: define positioning and messaging, conduct market and competitive analysis, enable sales, coordinate launches, gather customer insights, and measure product performance.

Own new business and account growth across hyperscalers, neoclouds, enterprises, and frontier AI labs in the Americas. Manage complex technical sales cycles, layered OEM/ODM and channel routes, capacity commitments, design-ins, pipeline forecasting, contracts, and executive relationships. Translate semiconductor performance, power, and TCO advantages into commercial outcomes while partnering with product, engineering, marketing, legal, and finance. Build a qualified pipeline through an existing customer network and represent the company at industry events.

Architects and delivers end-to-end agentic AI solutions using GCP, Python, LLMs, vector databases, and modern frontend frameworks. Designs scalable backend and cloud-native architectures, leads AI-focused workshops and proof-of-concepts, and establishes DevOps, microservices, and CI/CD practices. Collaborates with clients and engineering teams to translate business needs into technical roadmaps, while mentoring distributed teams and guiding architectural reviews.

Lead Strata from inception as co-founder, defining the vision for regulatory intelligence software, engaging enterprise customers, shaping the product roadmap, providing technical leadership for trusted AI agents, and recruiting teams across go-to-market, product, engineering, and customer success. The role requires early-stage B2B SaaS experience, hands-on LLM and agentic architecture expertise, and the ability to build products emphasizing accuracy, citations, auditability, and expert review.

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.

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.

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.

Analyze wafer-fabrication, equipment, sensor, metrology, and manufacturing data using statistical analysis, AI, and machine learning. Develop anomaly detection, yield prediction, root-cause, data pipeline, dashboard, and model-monitoring solutions. Integrate diverse manufacturing data sources, support experiments and process improvement, validate and deploy models, and communicate actionable engineering insights to technical and management stakeholders.

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.