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

Leads product design for Everand and Fable growth initiatives, designing onboarding, pricing, referrals, lifecycle, and subscription experiences. Partners with Product, Research, Engineering, Data, and Marketing to identify opportunities, run experiments, improve conversion and retention, and ship polished work. Uses research, competitive insights, data, prototyping, usability testing, and AI to guide decisions. Provides vision and strategy across growth and lifecycle while mentoring and collaborating with other designers.

Leads technical direction for Everand’s backend platform, including architecture, reliability, observability, CI/CD, databases, queues, and scalable distributed systems. Partners with product, design, analytics, web, mobile, and ML teams to deliver personalized reading and listening experiences. Mentors engineers, drives architecture reviews and modernization efforts, improves technical quality, and owns platform health, performance, cost, and resilience.

Lead cloud security architecture across AWS and GCP, strengthening identity, access management, workload protection, encryption, secrets management, and secure deployment paths. Build Terraform and policy-as-code guardrails, improve cloud threat visibility and detection, support threat hunting and incident response, and drive strategic security initiatives across engineering teams. Provide technical leadership, mentorship, and guidance while delivering measurable security improvements at scale.

Own iOS technical direction for Everand and Scribd growth, retention, and monetization features. Build subscription, paywall, and in-app purchase flows using StoreKit; ship experiments; integrate APIs; improve stability and reduce technical debt. Collaborate with backend, web, and Android teams, lead technical initiatives, and mentor engineers while delivering scalable Swift applications.

Build and scale fullstack Growth Platform systems, including self-service marketing tools, experimentation infrastructure, and customer and event-data integrations. Develop frontend and backend features, design and consume APIs, ensure scalability and maintainability, and collaborate with marketers, analysts, lifecycle teams, product managers, and engineers. Contribute to technical design, code reviews, testing, and process improvements while supporting attribution, data activation, and customer engagement.

Leads and scales Scribd’s Analytics Engineering organization, building high-performing teams and governed data foundations for AI-driven decision-making. Oversees canonical data models, semantic layers, quality, observability, documentation, security, lineage, and platform standards. Partners with engineering and business leaders to guide architecture, prioritize investments, and deliver reliable data products with measurable impact. Requires strong technical judgment, advanced SQL, modern data stack experience, cross-functional leadership, and 10+ years of relevant experience.

Leads performance and organic growth strategy across paid search, paid social, affiliate, SEO, and LLM-driven discovery for three brands. Manages channel experts, budgets, attribution, reporting, experimentation, and marketing technology to optimize acquisition efficiency and ROI. Partners with brand and creative teams on integrated campaigns, develops emerging channels, and applies data, AI tools, and unit economics to drive profitable growth.

Design, build, and operate Rust services powering Scribd’s large-scale Content Library and core infrastructure. Own features end to end, evolve Python tooling, optimize DataFusion, Parquet, S3, caching, and PostgreSQL/Aurora systems, and strengthen governance through lineage, authorization, and deletion controls. Lead cross-functional technical projects, support platform users, mentor engineers, improve developer workflows, and maintain production reliability through observability, on-call, and incident response.

Design, develop, and deploy machine learning and NLP solutions at scale. Work with cross-functional teams to build content classification, representation learning, search, and recommendation models using classical ML, deep learning, and LLMs. Process large datasets with Python, SQL, and Spark, and communicate results to stakeholders with clear documentation.

Lead and scale paid social advertising across Meta, TikTok, Reddit, and emerging platforms to drive user acquisition for subscription products. Own budgets, audience targeting, structured testing, creative collaboration, AI-accelerated experimentation, analytics, attribution and incrementality work, and conversion rate optimization across landing pages. Communicate results and build reusable playbooks for the performance marketing team.