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

Serve as the connection between a software product and legal users by demonstrating and onboarding customers, mapping legal workflows, designing AI prompts, delivering training, presenting at industry events, and sharing customer feedback with the product team. Requires legal practice and in-house experience, legal education, legal subject-matter expertise, hands-on AI tool use, customer-facing consulting skills, and willingness to travel approximately 25%.

Lead the technical direction of a productivity add-in and suite integrations. Design and build AI-assisted document editing features, including rewrites, tracked changes, and workflow automation. Define APIs across product and engineering teams, support desktop and web host applications, and own solutions from architecture through launch. Mentor engineers while maintaining high standards for code quality, developer experience, performance, and error handling.

Advise engineering teams throughout product development, evaluate AI-generated legal output, translate legal workflows into product specifications, write code using AI coding tools, and support sales teams with feature presentations. Requires a licensed attorney with law firm and in-house experience, at least five years of legal experience, substantive expertise in a legal area, and strong generative AI and technical skills.

Prospect and qualify business leads through email, phone, professional networking, and events. Research target accounts, conduct outbound outreach, respond to inbound interest, schedule discovery meetings, and maintain accurate CRM records. Design and test outreach sequences, report performance, and share market feedback with product and marketing teams.

Lead the architecture and technical direction of a document-editing plug-in and related productivity-suite integrations. Build AI-assisted editing and review features, coordinate front-end, API, design, backend, and document-engine decisions, and ensure reliable cross-platform performance. Drive features from design through production, manage host compatibility, improve developer tooling, and coach fellow engineers. The role also contributes to email integrations and next-generation AI interfaces.

Own the full enterprise sales cycle from initial conversation through signed contract. Generate pipeline, lead complex multi-stakeholder deals with technical, risk, and purchasing teams, establish a repeatable sales process, and share customer insights with leadership and product. The role requires experience closing enterprise software deals, selling to technical buyers, managing opportunities end to end, and carrying a quota.

Own backend-leaning product features from concept through release for a software platform. Build Python APIs, storage layers, and data-processing workflows, while contributing to frontend development. Design scalable REST APIs, support production services, and implement logging, alerting, and automated testing. Collaborate with design, research, deployment, product, and engineering teams in a small, cross-functional environment.

Design and build reinforcement learning environments, evaluation systems, reward functions, datasets, data pipelines, and ML infrastructure for computer-aided design tasks. The role converts expert mechanical and electrical engineering data into reliable model-training assets, automates scoring and content workflows, and runs experiments guiding technical and product decisions. Candidates need machine learning experience, physical-engineering domain exposure, engineering design software or vision-based ML familiarity, and hands-on reinforcement learning environment experience.

Build the sales funnel by researching enterprise prospects, conducting high-volume outreach, developing new territories, and securing qualified meetings for account executives and company leadership. The role requires resilience, self-direction, strong work ethic, and results-focused prospecting. Candidates may be recent graduates; prior business development or prospecting experience and selling to senior decision-makers are preferred.

Manage and grow large enterprise accounts by understanding customer product usage, demonstrating and configuring new capabilities, expanding accounts through trials and upselling, assessing opportunity value, and communicating customer needs to the product team. Build trusted relationships with security and risk stakeholders, proactively identify problems, and translate customer feedback into product improvements.