Top Tech Jobs & Startup Jobs in Los Angeles, CA

Leads legal strategy for structured finance and capital markets transactions, including debt facilities, warehouse lines, forward flows, securitizations, and secondary-market transactions. Negotiates commercial contracts, supports corporate governance and financing documentation, advises on regulatory compliance, manages outside counsel, and supervises corporate and commercial attorneys. Partners with executive, finance, treasury, and compliance teams to structure financing products and build scalable legal processes.

Re-engage previously funded small-business clients and convert paid-in-full accounts into new funding opportunities. The role involves high-volume outbound calling, consultative selling, Salesforce lead and funnel management, SMS and email follow-up, performance analysis, quota attainment, and collaboration with internal funding teams. The senior representative will also mentor junior staff, pilot new sales technology, and provide feedback on process improvements.

Conduct manual penetration tests and secure code reviews across web applications, APIs, AWS infrastructure, and AI systems. Develop AI-assisted security tooling, test LLM applications and agents, triage SAST findings, tune detection rules, and support security reviews before production. Communicate vulnerabilities, risks, and remediation priorities to engineering teams while helping establish the company’s application and AI security testing standards.

Lead the architecture and technical direction of Forward Financing’s core fintech platform. Design scalable distributed backend systems, guide cross-team initiatives, establish engineering best practices, resolve incidents, and mentor engineers. The role owns the technical roadmap and architectural vision while partnering across teams to improve reliability, observability, code quality, and delivery. Ruby on Rails expertise is required, along with strong communication, influence, agile development experience, and a broad backend or full-stack perspective.

Set the technical vision for data science, lead complex statistical and machine learning model development from concept through production, and architect scalable modeling platforms and pipelines. Develop credit risk, pricing, and loss forecasting models; establish model governance standards; partner with senior leaders; mentor data scientists; and communicate technical strategy to executives. The role emphasizes production deployment, monitoring, cloud architecture, and high-impact decision-making across the business.

Lead the design and execution of global total rewards programs, including compensation bands, benefits strategy, 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 total rewards systems and programs across a growing global organization.

Architects and develops AI-powered systems, tools, agents, backend services, APIs, and experimentation frameworks using foundational AI models. Integrates AI capabilities with microservices, AWS, Snowflake, and complex data systems while ensuring scalability, reliability, and maintainability. Translates business problems into technical solutions, prototypes AI applications, collaborates with product and engineering teams, evaluates emerging AI technologies, and documents system designs and integration patterns.

Conduct manual penetration tests and secure code reviews across web applications, APIs, AWS infrastructure, and AI systems. Develop AI-assisted security tooling, test LLM applications and agents, triage SAST findings, tune detection rules, support security reviews before production, and communicate risks and remediation priorities to engineering teams.

Manage a portfolio of small and medium business customers to grow relationships and identify additional capital solutions. Analyze business and financial histories, own the sales process from approval to close, use data to prioritize opportunities, and meet monthly quota in a fast-paced environment.

Lead and deliver end-to-end data science projects: design, build, deploy, and monitor ML/statistical models for credit risk, pricing, collections, and fraud. Partner with cross-functional teams to integrate models into production, set model development standards, mentor engineers, and maintain reliable ML pipelines and monitoring systems.