Senior Principal Software Engineer, Applied Generative AI

SoFi SoFi · Fintech · San Francisco, CA · Platform Infrastructure

Senior Principal Software Engineer to provide AI leadership at SoFi, focusing on applying Generative AI to software development and back-office operations. The role involves defining AI enablement strategy, championing best practices, leading vision for infrastructure, and overseeing build-over-buy approaches. Key responsibilities include technical leadership, strategic partnership with leadership, driving innovation in AI-assisted developer productivity, ensuring operational excellence, and mentoring engineers. Requires significant experience in applying Generative AI in enterprise software development, expertise in cloud platforms, and familiarity with agentic architectures.

What you'd actually do

  1. Technical leadership - Provide thought leadership around enabling and applying AI across the company.
  2. Strategic Partnership - Serve as a key strategic technical advisor to engineering and select business leadership, influencing roadmaps, participating in planning sessions, and ensuring alignment with business objectives.
  3. Innovate - Collaborate with cross-functional teams to drive innovation and advancements in AI assisted developer productivity flows.
  4. Operational Excellence - Be a subject matter expert, role model practitioner across the developer tooling domain including operational excellence. Drive observability strategy and practices, including SLOs, and guiding teams on critical incident resolution, root-cause analysis and remediation.
  5. Mentor - Collaborate with engineers across the Platform organization, provide mentorship, and expertise to enhance the overall technical capabilities of teams.

Skills

Required

  • Bachelor's or Master's degree in Computer Science, Software Engineering, Data Science, or a related technical field.
  • 15+ years of software development experience
  • Significant experience in the last several years applying Generative AI in software development and for end users, ideally in the context of a medium or large enterprise.
  • Expertise in public cloud platforms (AWS is preferred), containerization and orchestration (Kubernetes, Docker), and related technologies.
  • Deep understanding of modern development practices and CI/CD and how AI can change and improve on these practices to increase both quality and velocity.
  • Familiarity with ‘agentic’ architectures including SDKs, context engineering, MCPs, authorization .
  • Full stack “operator”: ability to both create and execute the business and product strategy; with clear objectives, but limited, ambiguous, or varied direction
  • Excellent communication and collaboration skills, with the ability to work effectively with both technical and non-technical stakeholders.

Nice to have

  • AWS preferred

What the JD emphasized

  • Provide AI leadership
  • AI enablement strategy
  • applying AI
  • AI assisted developer productivity flows
  • scaling the adoption of AI-enabled developer tooling

Other signals

  • AI enablement strategy
  • applying AI to software development
  • AI assisted developer productivity flows
  • scaling the adoption of AI-enabled developer tooling