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

Owns enterprise AI implementation engagements from kickoff through close, managing milestones, stakeholders, steering committee agendas, change management, executive communications, and value measurement. Partners with engineering teams to clarify priorities and requirements while keeping clients aligned. Builds delivery processes and playbooks as the practice scales. Requires client-facing credibility, project management experience, practical AI tool usage, and the ability to learn technical concepts quickly.

Build and operate the company’s B2B outbound engine, including agent-powered list building, enrichment, personalization, campaign execution, CRM management, sending infrastructure, deliverability, attribution, and measurement. Launch campaigns, improve messaging through testing and feedback, manage vendors, consolidate CRM data, and report on replies, meetings, and pipeline sourced. The role also requires AI automation, content generation, event campaigns, and technical integrations using APIs and webhooks.

Own the architecture and evolution of Crucible, building deployment systems, developer tooling, services, and platform abstractions. Lead technical roadmap development, solve complex deployment challenges, improve production reliability and security, and eliminate recurring operational issues. Provide hands-on technical leadership through system design, coding, code review, documentation, and engineering standards while improving developer productivity, deployment speed, platform adoption, and customer deployment success.

Lead the frontend of a proprietary AI platform: design and build reusable components, craft interaction patterns and workflows, prototype and deliver polished, high-performance UI experiences, and maintain platform building blocks for customer projects.

Own and deliver end-to-end production solutions: gather requirements, design architecture, implement frontend/backend/data, orchestrate LLMs/agents, perform production cutover, and define metrics. Interface with business stakeholders and operate in ambiguous, time-sensitive field contexts.

Build and own end-to-end production software from prototype to launch: frontend (React/TypeScript), backend (Python, APIs, Postgres), data models, integrations, LLM orchestration, deployment, and operational reliability for LLM-powered applications.