Top Tech Jobs & Startup Jobs in San Francisco Bay Area, CA

Analyzes computer systems and business processes, gathers and validates stakeholder requirements, models workflows using BPMN or UML, and uses SQL for data analysis and troubleshooting. The role supports process optimization, technical issue resolution, virtual collaboration, and validation of AI training data and scenarios for customer projects.

Provides empathetic, efficient customer support across multiple channels; documents interactions in CRM software; analyzes issues and proposes solutions; applies product knowledge to educate users; shares customer feedback and sentiment trends; develops support documentation; and supplies scenario-based input to train AI systems. Requires at least three years of professional customer support experience, strong communication and problem-solving skills, CRM proficiency, and experience managing complex cases.

Provide subject-matter input on criminal law to train AI: review and analyze court filings and case materials, draft and annotate scenarios, evaluate AI outputs for legal accuracy and ethics, flag nuanced issues, and collaborate remotely to deliver actionable feedback while staying current on statutes and case law.

Design, simulate, verify, and validate analog, digital, power, mixed-signal, or RF circuits for an AI training project. Translate requirements into schematics, netlists, HDL, models, and simulation inputs; automate workflows with Python; analyze electrical results; perform corner and Monte Carlo analyses; compare simulations with physical measurements; troubleshoot hardware and review AI-generated circuit solutions. Requires real fabricated or shipped circuit-design experience and command-line or programmatic EDA expertise.

Conduct quantitative and qualitative research, analyze complex business scenarios, gather requirements, and synthesize stakeholder perspectives into actionable recommendations. Evaluate data using tools such as Excel or SQL, identify process improvements, and produce clear reports, memos, business cases, and documentation. Collaborate with stakeholders through written communication and contribute analytical content to help train AI systems.

Reviews, develops, validates, and refines dashboards, reports, visualizations, calculations, data sources, KPIs, and analytical workflows across BI platforms. The role documents findings, provides structured feedback, troubleshoots reporting accuracy, and evaluates AI-powered agents and workplace connectors used in analytics processes.

Develop and maintain scalable Java backend systems using Spring Boot and microservices architecture. Collaborate with customer teams, review specifications, write clean code, participate in code reviews, document solutions, and troubleshoot and optimize backend performance, reliability, and security. The role also contributes technical expertise to training next-generation AI systems, though prior AI experience is not required.

Develop and maintain backend services and RESTful APIs using C# and .NET. Design and optimize MySQL schemas and queries, troubleshoot production and staging issues, improve performance and scalability, document architecture, and uphold code quality and security. Collaborate with cross-functional teams in a fully remote environment while contributing to development best practices and continuous improvement.

Identify companies with valuable operational data for AI training and evaluation, conduct outbound prospecting, run discovery calls, explain data partnership value and technical concepts, address privacy and ownership concerns, negotiate terms, close B2B deals, manage the sales pipeline, and coordinate partner onboarding with internal teams.

Build reinforcement learning environments to evaluate AI systems on software engineering tasks involving MCP tools. Responsibilities include creating reproducible environments, deterministic verification, golden reference solutions, bug fixes, feature development, codebase refactoring, and performance optimization. The role is remote, flexible, contract-based, and output-focused, with no prior AI experience required.