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

Design, build, deploy, and maintain AI-powered production systems directly with customers. The role spans backend services, integrations, orchestration, data pipelines, cloud infrastructure, testing, monitoring, and troubleshooting. Engineers translate ambiguous operational needs into scalable technical solutions, own deployments end to end, collaborate with Product and Core Engineering, and convert customer learnings into reusable platform capabilities. The position requires strong software engineering, applied AI, systems, infrastructure, communication, and customer-facing skills.

Own the analytics lifecycle from data ingestion, ETL, modeling, orchestration, validation, and warehousing through BI dashboards and actionable insights. Build SQL/Python analyses and automation, define trusted metrics, quantify customer ROI, improve data quality, and support customer-facing presentations. Prototype machine learning models for product and business problems while designing scalable analytics infrastructure and partnering with Product, Engineering, and CX teams.

Own Laurel’s technical marketing infrastructure, including website performance, SEO, analytics, HubSpot automation, paid LinkedIn and Google campaigns, attribution, reporting, and AI-powered advertising workflows. Build and optimize marketing automation, AI agents, tracking systems, dashboards, and data processes that connect channel performance to pipeline and revenue. Partner with AI Engineering to develop and improve automated marketing solutions.

Lead and scale a sales enablement function: own onboarding, build pitch/content libraries, design certification, coach sellers, run enablement cadence, translate product and competitive updates, and partner with Product Marketing, RevOps, and Sales leadership to align enablement to pipeline and win/loss signals.

Lead full-cycle GTM recruiting (AEs, CSMs, SDRs, Solutions Engineers, sales leadership). Build outbound sourcing, partner with hiring managers, run structured assessments and calibrations, close competitive candidates, manage 10–15 active reqs and deliver ~6–10 hires per quarter across multiple geographies.

Build and maintain sales enablement assets and technical product collateral; translate product capabilities into value-based messaging; support competitive intelligence; partner with sales to close field gaps; own demo scripts, objection-handling, launch enablement, and a maintained enablement content repository.

Lead and build the accounting function: own accounting operations and close processes, design scalable policies and controls, manage audits and external accounting partners, drive process automation and AI efficiencies, hire and develop the accounting team, and partner with the CFO on fundraising, scaling, and long-term public company readiness.

Designs, builds, and deploys AI-powered productivity systems for engineering teams. Responsibilities include developing CI/CD pipelines, integrating platforms and enterprise systems, evaluating emerging AI and infrastructure tools, improving developer workflows, collecting telemetry and feedback, driving adoption, and partnering with engineering leadership. The role requires strong platform, infrastructure, DevOps, cloud, Linux, and systems engineering expertise, plus hands-on experience with Kubernetes, AWS, Terraform, Go, TypeScript, and on-call operations.

Supports client integrations, DevOps monitoring, ERP and practice management system transitions, and technical escalations. Builds and customizes Boomi processes, validates data flows, monitors integration health, investigates alerts, performs root-cause analysis, and resolves synchronization issues across APIs, databases, ERP, PMS, and SaaS environments. Communicates with client technical teams during incidents and migrations, coordinates fixes, documents recurring issues, and improves integration performance and reliability.

Support and maintain integrations between Laurel and client ERPs/PMS (notably SAP S/4HANA). Build and test Boomi processes, monitor integration health, respond to alerts, troubleshoot data flows, perform root cause analysis, and serve as Level 2 escalation. Coordinate migrations, communicate with client technical contacts, document processes, and collaborate with Principal Engineers and product teams to resolve complex issues and improve reliability.