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

Leads client engagements from scoping through completion, managing scope, timelines, quality, contributors, and deliverable specifications. Supports commercial outcomes and internal operational initiatives involving analysis, coordination, building, and execution. Requires hands-on engineering experience in chemical, biomedical, or life-sciences fields, strong evidence-based reasoning, and on-site work in San Francisco.

Serve as the primary contact for over 100 B2B technology accounts, resolving customer questions and technical issues through phone, email, and chat. Coordinate escalations with account, product, and engineering teams; maintain customer satisfaction; manage knowledge base updates; develop platform expertise; and relay customer feedback to improve products.

Conduct outbound prospecting through email, phone, and professional networking platforms; engage prospective buyers, understand their challenges, and demonstrate the value of technology solutions. Collaborate with product, design, and leadership teams to align offerings with customer needs, maintain key account relationships, and communicate effectively with technical and non-technical audiences.

Leads commercial third-party data acquisition, including sourcing strategy, supplier outreach, complex contract negotiations, licensing terms, renewals, compliance, budget oversight, executive reporting, and associate team management. Collaborates with legal, engineering, operations, and research teams to ensure purchased data is valuable, technically suitable, and compliant with copyright, privacy, and governance requirements.

Lead end-to-end delivery of customer projects, including system design, rollout, configuration, tuning, and hands-on support. Partner with senior leaders and operational teams to discover needs, translate them into technical solutions, and deepen product adoption. Build small workflow tools using Python and JavaScript, share customer insights with product leadership, and help shape the platform roadmap. The role requires strong communication, client-facing engineering experience, and adaptability in a fast-changing environment.

Own and build core backend services and infrastructure for sandboxed workloads, gateways, and task orchestration. Design production systems from zero to one, scale services, ship customer-facing features quickly, and make autonomous technical decisions. The engineer will gradually assume backend ownership from a senior engineer while collaborating closely with customers and the team.

Own product features end to end across backend services and user interfaces. Build automated matching and scheduling systems, predictive analytics for workforce retention, and operational data pipelines. Translate user needs into working releases, establish reusable coding patterns, and use AI-assisted development tools. The role requires strong full-stack engineering, product judgment, interface design, independent execution, and frequent in-person collaboration in a demanding onsite environment.

Build the outbound sales pipeline as the first go-to-market hire at an early-stage AI software company. Generate qualified leads and booked meetings through cold email, LinkedIn, and social direct messaging. Test and refine outreach approaches, identify high-performing methods, and potentially build and lead a sales team as the company grows.

Design and build realistic simulated workplace environments, evaluation tasks, benchmarks, graders, and scoring systems for training and assessing AI models. Generate synthetic records, files, and communications; prevent models from exploiting evaluation systems; align benchmarks with real-world performance; and convert user feedback into new test cases. The role is early-career and emphasizes reinforcement learning or model post-training experience.

Build the execution layer of an AI-driven product, including persistent context, autonomous operation, evaluation systems, infrastructure, and user experiences across documents, messaging, and mobile. The role requires end-to-end architectural ownership, product and interface design instincts, familiarity with AI assistants, daily use of AI tooling, and experience creating measurement methods that influence team decisions.