Top Tech Jobs & Startup Jobs in San Francisco, CA

Drive revenue by managing and expanding relationships with large enterprise accounts. Qualify opportunities, negotiate contracts, close deals, and collaborate with product, marketing, and customer success to meet sales targets and ensure long-term customer satisfaction.

Build, harden, deploy, and operate LLM-powered micro-apps and agents on a governed GCP platform. Integrate AI with business systems (Salesforce, Slack, NetSuite), implement CI/CD, secrets and identity controls, monitoring, and automated maintenance. Create retrieval pipelines, evaluation and observability for model quality, and partner with stakeholders to move proofs of concept into production.

Manage and qualify inbound leads, serve as first point of contact for prospects, nurture relationships through the sales qualification process, use CRM and Microsoft Office tools, and support progression into inside sales roles while working hybrid from specified offices.

Lead strategy and delivery of AI-powered, agentic features for a SaaS insurance product. Define roadmaps, validate hypotheses through research and experiments, collaborate with engineering and data science, track KPIs and ROI, drive go-to-market and adoption, mentor junior PMs, and prioritize backlog to maximize customer value and retention.

Lead and operationalize the data governance program, including stewardship adoption, data lifecycle controls, metadata/catalog management, data quality improvements, training, KPI tracking, and cross-functional issue resolution.

Partners with engineering and technical leaders to recruit, source, screen, and hire talent. Manages the full recruiting lifecycle, advises on market trends and compensation, improves hiring processes, maintains ATS data quality, analyzes recruiting metrics, and mentors teammates to support efficient, inclusive hiring.

Design and implement security controls for LLMs and generative AI systems. Conduct threat modeling, architecture reviews, and vulnerability remediation for ML pipelines. Secure training, fine-tuning, and inference infrastructure, including containers, Kubernetes, and cloud/GPU environments. Develop policies, runbooks, and training; evaluate vendor AI services; assist with proofs-of-concept and incident response for AI-specific threats like prompt injection and model poisoning.

Sell Applied/Ivans technology to P&C carriers and MGAs by building and owning a sales pipeline, executing consultative full-cycle sales, developing targeted strategies, negotiating contracts, closing deals, and collaborating with Solutions and Product teams. Represent the company at industry events and consistently meet revenue targets.

Manage a book of strategic carrier and broker accounts post-sale to drive adoption, utilization, renewal, and expansion. Build senior relationships across underwriting, operations, and IT; run QBRs and executive reviews; deliver product and AI/LLM-focused demos; coordinate cross-functionally; and travel for onsite workshops and executive sessions (up to 50%).