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

Lead the quality practice for an AI voice interface product by developing automated tests across desktop, mobile, backend services, and integrations. Establish continuous regression testing and CI/CD release gates, investigate real-world voice workflows and failures, prioritize risk-based testing, and provide release recommendations. Partner cross-functionally throughout development, improve coverage from incidents and defects, and coach QA teammates while remaining hands-on.

Lead Wispr Flow’s security assurance and GRC programs across SOC 2, ISO 27001, privacy, risk management, and enterprise customer requirements. Own customer security reviews, questionnaires, escalations, Trust Center content, audit evidence, controls, remediation, and compliance tooling. Partner with Engineering, Product, Legal, Sales, and Customer Success to address security blockers, improve automation, communicate AI security and privacy practices, and translate customer feedback into product requirements.

Build and lead foundational revenue operations across product-led and sales-led motions. Own forecasting, pipeline, lead routing, deal desk, quote-to-cash, GTM data modeling, funnel reporting, rep enablement, and customer journey processes. Develop AI-native agentic workflows using code, CRM, warehouse data, and modern GTM tools to automate enrichment, hygiene, research, and deal processing while driving measurable revenue outcomes.

Own and build complex detection, inference, state, and delivery systems across AI products. Instrument ambiguous quality problems, establish correctness without reliable ground truth, define meaningful quality metrics, and make tradeoffs across imperfect signals and user impact. Partner with product and platform teams to place systems appropriately and turn persistent quality issues into reusable, measurable solutions.

Owns product growth across onboarding, first dictation, and habit formation. The role ships rapid experiments, evaluates funnel metrics, improves experimentation reliability through randomization and instrumentation, and partners across teams to close product funnel gaps. Success requires data-driven decision-making, production-quality execution, and ownership of ambiguous growth problems.

Build verification and evaluation systems that allow AI agents to determine when work is complete. Develop testing environments, convert failures and human feedback into evaluation signals, improve agent context and memory delivery, and operate the agent fleet as a production system. The role spans application code, infrastructure, testing, measurement, and ambiguous problem-solving. Prior voice, model training, or product-domain experience is not required.

Build and own polished enterprise product experiences across administration, permissions, user management, analytics, and complex workflows. Develop responsive React and TypeScript interfaces, work across APIs, data models, and backend services, and take features from customer requirements through production. Improve usability, accessibility, performance, and maintainability while applying strong product and design judgment in ambiguous situations.

Lead customer deployments from discovery through adoption, building and debugging production solutions across APIs, integrations, identity, data, and customer environments. Partner with technical and business stakeholders, communicate clearly under pressure, solve complex system issues, and turn recurring customer needs into product improvements, reusable integrations, and deployment playbooks.

Architect, build, and operate backend systems that enable enterprise customers to adopt and scale Wispr. Responsibilities include multi-tenant architecture, APIs, data models, migrations, distributed workflows, enterprise identity and access management, auditability, privacy controls, observability, and production operations.

Own the architecture of Wispr’s macOS platform and build a reliable screen-context engine supporting dictation, Notetaker, Instruct Mode, and future products. Establish technical direction across accessibility, native integrations, memory, state, and background behavior; solve performance, correctness, privacy, and cross-application issues; and create durable platform foundations for other engineers.