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

Leads a team of five executive assistants, supports 2–3 C-suite executives, and establishes standards for executive administration. Responsibilities include coaching, hiring, process and playbook development, AI adoption, coverage planning, travel and event coordination, vendor management, executive scheduling, meeting preparation, stakeholder communication, expense management, and confidential information handling.

Lead engineering teams responsible for Life360’s critical platforms, including location and messaging, cloud infrastructure, identity, and partner ecosystems. Set technical direction, modernize legacy systems, improve reliability and scalability, establish engineering metrics, and develop engineering managers and technical leaders. Partner with Product, Security, Data, and Engineering leadership to align technical investments with business outcomes while supporting secure, high-performing systems serving millions of users.

Build and maintain premium mobile features, subscription and in-app purchase flows, paywalls, pricing experiences, and advertising functionality for Life360’s consumer app. Own feature quality, performance, reliability, experimentation, and incident response at 100M+ user scale. Collaborate with product, design, data science, and analytics teams; use AI coding agents extensively; contribute to architecture and code reviews; mentor engineers; and help evolve AI-native engineering practices.

The Director of AI Platforms will lead the AI Platforms team, define its roadmap, and build shared infrastructure for model access, agent runtimes, MCP integrations, evaluation, identity, inference, and cost controls. The role drives adoption of agentic engineering practices, extends AI platforms to consumer-facing products, partners with Security, Privacy, and Legal on safeguards, and measures outcomes such as quality, cost, adoption, and delivery speed. The leader will hire and develop engineers while providing hands-on technical direction.

Build and own Android growth and monetization experiments across subscriptions, pricing, advertising, purchases, and upgrade flows. Partner with product, design, data science, and analytics to instrument experiments, manage staged rollouts, monitor performance, and act on results. Use AI tools throughout development, contribute to Android architecture and engineering practices, participate in on-call support, mentor engineers, and help scale reliable mobile experiences to tens of millions of users.

Own revenue-focused data science from opportunity sizing through production ML. Investigate and measure product changes, build and operate batch and online ML systems for personalization, experimentation, and automation, and partner cross-functionally to integrate models into user-facing products. Establish monitoring, lineage, reproducibility, and security practices; improve data pipelines; mentor data scientists; and define ML development best practices while using AI tools to accelerate delivery.

Advise ads product, engineering, marketing, and sales teams on privacy, consumer protection, content regulation, and product development matters. Counsel the advertising business on GDPR, CCPA, international regulations, content policies, and risk management. Monitor regulatory trends and collaborate cross-functionally to support compliant ad-tech products and services.

Build and own Android growth and monetization experiments across subscriptions, advertising, purchases, and upgrade flows. Partner with product, design, data science, and analytics to instrument experiments, evaluate results, and ship reliable experiences at consumer scale. Use AI-native workflows for specification, coding, testing, and review; improve mobile engineering practices; contribute to architecture and code reviews; participate in on-call; and mentor engineers.

Build and operate scalable backend services for connected devices, including device connectivity, telemetry ingestion, health monitoring, command and control, and data pipelines. Collaborate with firmware, mobile, and product teams on APIs and workflows. Use AWS, microservices, streaming systems, observability tools, and AI coding agents to deliver reliable features, participate in incident response, and improve automation and engineering practices.

Design and run high-volume experiments across subscription and monetization experiences, including pricing, trial conversion, SKU routing, churn prevention, and win-back. Translate ambiguous briefs into testable hypotheses, collaborate with product, engineering, data science, and content teams, define success metrics, interpret results, and present learnings. The role requires strong visual and interaction design craft, animation skills, organized Figma files, proactive ideation, and effective use of AI and experimentation tools.