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

Own the technical pre-sales process for enterprise customers, from discovery and solution design through demos, architecture reviews, proposals, and deal close. Build tailored AI agent prototypes, explain business and technical value, collaborate with CX, IT, security, procurement, and executives, and support account expansion after the sale. Mentor sales engineers, create reusable assets, and use AI tools to improve technical sales workflows.

Own the end-to-end technical pre-sales process for strategic enterprise accounts, including discovery, solution design, demos, architecture and security reviews, technical proposals, and customer presentations. Build executive and technical relationships, support launches and account expansion, mentor sales engineers, develop strategic-deal playbooks, coordinate internal teams, and communicate customer insights to Product leadership. The role requires selling complex AI products to customers with $1M+ deal sizes.

Partners with enterprise sales teams to win and expand financial services customers. Leads the technical pre-sales cycle, including discovery, solution scoping, business-value articulation, platform design, demonstrations, architecture reviews, prototypes, and technical proposals. Collaborates with Sales, Product, and Agent Engineering to improve customer solutions and scale successful industry motions.

Serve as the technical partner to enterprise sales teams, leading discovery, solution design, demonstrations, architecture reviews, prototypes, and technical proposals. Build tailored AI agent solutions, explain business value to technical and non-technical stakeholders, manage multiple concurrent deals, and collaborate with Sales, Product, and Agent Engineering to improve Sierra’s platform and go-to-market strategy.

Own the end-to-end technical presales process for enterprise customers, from discovery and solution design through tailored AI agent demos, architecture reviews, proposals, and deal close. Partner with sales, customer technical teams, executives, procurement, and security stakeholders. Support launches, expansions, and account growth after the sale, while mentoring newer sales engineers and developing reusable industry assets.

Own the technical pre-sales process for enterprise public-sector customers, partnering with sales teams to discover use cases, design and demo AI agent solutions, lead architecture reviews, and articulate business value. Build working prototypes, engage technical and executive stakeholders, support launches and account expansion, mentor sales engineers, and create reusable industry assets. The role requires strong enterprise sales engineering experience, relationship-building, technical communication, and effective use of AI tools.

Support and evolve global compensation programs through analysis, market benchmarking, compensation planning, offer optimization, stock plan administration, and scalable tools. Partner with Recruiting, Legal, People teams, and business leaders while maintaining compensation bands, equity frameworks, dashboards, and self-service experiences. Use AI and automation to improve workflows, data accuracy, operational efficiency, and compensation insights across international markets.

Design and lead global onboarding programs for Account Executives and Sales Engineers. Deliver role-specific training, certifications, workshops, and AI fluency education; establish ramp metrics; use AI to scale enablement and coaching; partner cross-functionally to maintain accurate content; recruit subject-matter experts; gather feedback; and continuously improve the program across regional teams.

Build scalable data foundations and personalization systems for AI agents. Responsibilities include real-time eventing, streaming and batch ETL, Iceberg lakehouse infrastructure, OLAP querying, orchestration, experimentation, long-term agent memory, customer data platform primitives, analytics products, and optimization loops. The role may focus on platform engineering or full-stack product engineering, including ML-powered personalization and data visualization.

Build enterprise platform capabilities for identity, access management, integrations, extensibility, scalability, security, compliance readiness, reliability, and operational excellence. Develop reliable and secure backend-leaning full-stack systems for complex customer environments and AI-powered enterprise SaaS products.