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

Own post-sale relationships with business accounts from trial conversion through renewal, including onboarding, adoption, expansion, and customer calls. Convert proof-of-concept trials into paid contracts, communicate feedback to product and leadership, align customer objectives with platform capabilities, and build the customer success function and processes from scratch.

Build and optimize signup, onboarding, activation, and conversion experiences for a developer-facing SaaS product. Develop full-stack features with TypeScript, Node.js, and React; instrument user funnels; run A/B tests; analyze metrics; and iterate on experiments. The role requires production experience with large language models, prompting, tool use, and inference pipelines, plus a track record of improving growth metrics and shipping developer-focused products.

Handle shareholder-side securities class action litigation from filing through resolution. Responsibilities include managing cases, drafting briefs and motions, developing legal theories, contributing to case strategy, researching securities law, and tracking case-law developments. The role requires strong class action experience, persuasive legal writing, analytical judgment, a JD, and office attendance in San Francisco or Boston three days weekly.

Own and operate production infrastructure for large-scale automated web data collection. Design proxy pools, session handling, isolated outbound traffic, browser identity systems, and automated challenge handling. Improve request success rates against anti-bot defenses, manage reliability and costs, investigate intermittent failures, and provide full production ownership including on-call responsibilities.

Own the design, development, and operation of a large-scale search platform. Improve retrieval quality and ranking, build indexing and query-serving systems, reduce latency and query costs, and manage services through launch, monitoring, and refinement. The role requires backend programming, search relevance expertise, performance optimization, and data-driven iteration. It is a full-time, on-site position in San Francisco or Toronto.

Serve as the technical expert throughout sales opportunities by conducting discovery, designing solutions, demonstrating products, answering technical questions, building prototypes, and writing proposals. Partner with revenue, product, and engineering teams to advance deals and relay prospect feedback. The role requires hands-on coding, practical AI experience, customer-facing technical communication, and on-site work in San Francisco five days per week.

Build qualified sales pipeline through outbound prospecting and inbound lead qualification. Research target accounts, personalize outreach, qualify leads, educate technical and business buyers on AI inference and model-serving products, meet pipeline targets, and collaborate with Sales and Marketing. The role requires full-time onsite work in New York City or the San Francisco Bay Area.

Internal, unpublished integration fixture used to verify that Workable applications transfer candidate identity, LinkedIn profile URLs, metadata, and resumes into Raydar Applicant Hub and Paraform. It is not an employment opportunity and offers no compensation or benefits. Production roles must be cloned, renamed, populated with an actual description, and configured with mandatory candidate name, email, resume, and public LinkedIn profile fields.

Owns the end-to-end improvement of machine learning models after initial training, including compute setup, dataset preparation, simulated environment design, and automated self-improving workflows. The role combines applied AI research with software engineering, requiring expertise in reinforcement learning, evaluations, interpretability, PyTorch, ML pipeline debugging, and curated dataset production.

Leads customer implementations of AI-driven software from scoping through launch, serving as the primary technical contact for senior stakeholders. Builds AI agents using Python, prompts, model integrations, and rapid prototyping; develops customer integrations through APIs; and partners with platform engineers to improve product capabilities. Documents implementation lessons and helps establish a client-facing engineering function.