Top Tech Jobs & Startup Jobs in San Francisco, CA

Analyzes sales performance, pipelines, forecasts, and trends to support leadership decision-making and revenue growth. Builds Tableau and Salesforce dashboards, performs ad hoc analysis, evaluates sales channels, supports test-and-learn initiatives, and identifies technology improvements including AI tools. Partners cross-functionally with Finance, Marketing, Technology, Analytics, and leadership. Also administers Salesforce, compensation plans, sales contests, and performance leaderboards.

Senior legal leader responsible for structured finance, debt capital markets, borrowing facilities, forward flow agreements, securitizations, and secondary market transactions. The role also oversees commercial contracting, corporate governance, regulatory alignment, outside counsel, and a team of corporate and commercial attorneys. Responsibilities include negotiating financing arrangements, monitoring compliance and covenants, structuring financial products, developing legal processes, and providing business-oriented advice in a fast-growing fintech environment.

Re-engage paid-in-full small-business clients and convert them into renewal funding opportunities through high-volume outbound calls, SMS, and email. Manage Salesforce lead queues, maintain accurate funnel data, meet activity and revenue quotas, analyze conversion performance, collaborate with funding teams, mentor junior representatives, and pilot new sales technology. Success requires strong consultative selling, persistence, financial-document communication, and disciplined SLA and pipeline management.

Principal Software Engineer responsible for architecting and leading development of scalable, reliable backend platforms. The role sets technical direction, leads cross-functional engineering initiatives, promotes architectural and operational excellence, resolves incidents, and mentors engineers. Requirements include 10+ years of technical leadership experience, deep expertise in distributed backend systems and scalable architectures, Ruby on Rails experience, strong communication and influence, agile development experience, and familiarity with front-end architecture or full-stack systems.

Sets the technical vision for data science, leads complex statistical and machine learning initiatives from concept through production, and architects scalable modeling ecosystems for credit risk, pricing, and loss forecasting. The role partners with senior leaders, establishes model development standards, builds monitoring frameworks, mentors technical talent, and communicates strategy to executives. Key responsibilities include production deployment, model validation, roadmap development, and delivering measurable business impact across financial services.

Lead the design and execution of global total rewards programs, including benefits strategy, geographic compensation bands, equity and incentive plans, job leveling, pay equity, and annual compensation cycles. Advise executives, HR business partners, and talent acquisition using market data, financial modeling, and internal equity analysis. Optimize compensation technology and support scalable rewards programs across the United States and Canada.

Architect and develop backend systems, APIs, tools, and agents that integrate foundational AI models into scalable business solutions. Build AI workflows, automation, data pipelines, experimentation frameworks, and integrations across AWS, Snowflake, microservices, and complex technology stacks. Collaborate with product, data science, and frontend teams to prototype and deploy AI capabilities while evaluating emerging frameworks, documenting designs, and considering reliability, privacy, and responsible AI.

Leads security operations by building and managing a security engineering team, owning incident response and incident command, tuning CrowdStrike detections, and developing detection coverage across endpoints, SaaS, identity, cloud, and network signals. The role oversees vulnerability and patch management, cybersecurity risk assessments, external exposure controls, reporting standards, and AI security strategy. It requires hands-on detection engineering, incident response, AWS monitoring, SaaS security, automation, and executive communication.

Lead end-to-end data science initiatives including designing, deploying, and monitoring production ML models for credit risk, pricing, collections, and fraud. Partner cross-functionally to integrate models, set development standards, mentor team members, and maintain production pipelines and monitoring systems to drive measurable business impact.

Manage a portfolio of small and medium businesses to grow relationships and provide additional capital solutions. Analyze business and financial histories, advise on product fit, use data to prioritize opportunities, own the sales process from approval to closing, and meet monthly quotas while collaborating with underwriting and other account executives.