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

Design, build, train, and deploy AI agents and machine learning systems for complex technical data. Develop context handling, indexing, search, and information retrieval workflows; integrate AI systems with enterprise platforms; and ship reliable production features. Collaborate with customers and engineers, prototype rapidly, influence architecture and product direction, and help establish engineering culture as an early engineering hire.

Serve as the first engineer, owning product and technical direction across the full stack. Build reliable production systems, measurement and attribution infrastructure, automation and data retrieval systems, AI agents, integrations, and new product surfaces. Improve workflow reliability through queues, retries, and observability while working directly with customers to prioritize and ship features. Help establish engineering culture and architecture in an early-stage, on-site startup.

Designs and builds sales and marketing systems for external clients. Responsibilities include onboarding and advising client leadership, developing ideal customer profiles and target lists, launching outbound and signal-driven campaigns, integrating tools through APIs and light coding, and creating reusable playbooks. The role also helps define the pricing, tooling, and team structure for a new client services business line.

Own the technical delivery of reliable, scalable software across backend services and applications. Architect high-throughput systems, handle large datasets, launch and refine applications, and contribute to technical direction and engineering practices. The role requires pragmatic execution in a fast-paced, ambiguous environment, collaboration with peers, and participation in recruiting activities including sourcing, interviewing, and making offers.

Build and own backend infrastructure, data storage layers, scalable architecture, and production features for a financial technology platform. The engineer will design systems, extend and harden the codebase, ship production-quality code with significant autonomy, collaborate with founding leadership, and help shape engineering culture and future hiring. The role is onsite in San Francisco with opportunities for technical leadership.

Design datasets, evaluation methods, scoring rubrics, and reward signals for machine learning model training. Build data pipelines for natural and synthetic training material, develop quantitative methods to assess dataset quality and model impact, study annotation behavior, run controlled experiments, and collaborate with research partners to define training and evaluation specifications.

Own end-to-end product development across data storage, front-end interfaces, developer tooling, SDKs, command-line experiences, testing environments, and access management. Collaborate directly with customers to define requirements, prioritize features, and iterate on solutions. Build production software spanning databases through the browser, with opportunities to apply LLMs and agents in a fast-moving, customer-focused environment.

Build backend services, data pipelines, retrieval systems, and machine learning inference pipelines for large-scale video, audio, and text data. Integrate language and vision-language models into production, deploy secure distributed systems, and own projects from architecture through release. The role also requires clear technical communication, strong Python skills, backend scaling expertise, and comfort in a fast-paced startup environment.

Design, build, and deploy production AI systems that process large volumes of unstructured healthcare records. Translate customer problems into technical solutions, develop retrieval-based pipelines and multi-agent workflows, integrate healthcare data standards, and own monitoring and optimization. Partner with customers, leadership, product, and safety teams while identifying opportunities to expand AI adoption.

Own and scale automated sourcing and outreach programs that attract and onboard professionals into a large community. Build recruiting pipelines, engage candidates across industries, manage multiple hiring streams, analyze funnel performance, run growth experiments, recruit experienced specialists, and develop automation systems. Partner directly with company leadership on strategy and execution while driving brand awareness across channels in a fast-paced startup environment.