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

As a Senior Staff Site Reliability Engineer, you will lead the SRE team, advocate best practices, ensure resilience in cloud architecture, and mentor team members.

Develop and optimize dbt infrastructure, implement scalable data models, and ensure consistent business logic across teams at Ironclad.

Lead marketing technology and operations owning the full martech stack, data foundations, AI-powered automation, and scalable campaign and funnel processes. Partner cross-functionally, manage pipeline reporting, and lead a team of GTM engineers and ops specialists to operationalize brand, demand, and community programs.

Lead and enhance IT Operations, directing a team of engineers, managing end-user support, and overseeing identity access operations in a fast-paced environment.

Lead and scale a Revenue Enablement team to improve seller productivity, manager effectiveness, and AI readiness. Build programs (certifications, SKO support, coaching, reinforcement) tied to measurable revenue outcomes and partner cross-functionally to align messaging and execution.

The Technical Lead Manager at Ironclad leads a team of engineers, manages product delivery, advises on technical contributions, and drives operational excellence while aligning with company strategy and culture.

As a Principal Engineer, you will architect and evolve AI-powered solutions, collaborate cross-functionally, and lead technical discussions while mentoring engineers.

The Solutions Engineer will work with prospects to understand their needs, design and present customized Ironclad platform demonstrations, and collaborate with sales and product teams to drive customer engagement and product development.

The Staff Systems Engineer designs and builds enterprise automations and integrations, focusing on reliability and scalability, while mentoring engineers and fostering technical standards across teams.

Lead design and delivery of high-priority AI initiatives across product and platform boundaries. Rapidly prototype and launch AI features, unblock teams, mentor engineers, and shape production-grade LLM systems (retrieval, evals, prompting, orchestration). Collaborate with product, design, and domain experts to turn customer needs into shipped product.