Software Engineering Manager, Digital Identity — Access & Rights

SoFi SoFi · Fintech · Seattle, WA · Engineering

Software Engineering Manager for the Digital Identity — Access & Rights team at SoFi. This role involves leading and growing a senior team responsible for Entitlements and Authorization platforms, which are critical Tier-0 services. The manager will drive technical strategy, ensure operational excellence, and collaborate across departments. The role emphasizes hands-on technical depth, coaching engineers, and utilizing modern AI tooling for productivity.

What you'd actually do

  1. Lead and grow your team while maintaining or improving the team’s velocity. Manage performance with care and high standards, including the hard conversations.
  2. Own the planning, technical output, and delivery for the Digital Identity - Access & Rights team. Own operational excellence for two Tier-0 platforms. Set and defend SLOs, while holding the on-call posture accountable, and treat production quality as a management responsibility, not an IC concern. Review design documents, push back on senior engineers when the architecture does not hold up, pair with your team in AI-augmented coding sessions, and ship production code when the situation demands it.
  3. Establish and leverage strong relationships across the department and cross-functional leadership teams, partnering closely with product and other engineering teams to integrate solutions and define product and technical strategy.
  4. Operate with a high degree of independence to solve ambiguous and complex technical problems. Drive initiatives from inception to completion, contributing to the long-term architectural vision and continuous improvement of the identity platform.
  5. Write well, and use AI to write faster. You will personally own incident reviews, roadmap updates, as well as promotion cases to shape the executive narrative for the platform.

Skills

Required

  • 8+ years of experience designing, building, and operating scalable, mission-critical backend systems, with 2+ years directly managing engineers.
  • Proven track record running a high traffic Tier-0 or equivalent critical platform: defined SLOs, owned on-call, led major incident reviews, and drove measurable reliability improvements.
  • Deep experience with platform-style engineering: API contracts, versioning, backward compatibility, consumer migration, and deprecation discipline. You have managed a platform team with many downstream consumers, not just a feature team.
  • Active, daily user of modern AI coding tools (Claude Code, Cursor, Copilot, or equivalent). Concrete examples of how you have used AI to accelerate your own output or your team's throughput.
  • Demonstrated ability to drive outcomes across team boundaries without escalation authority. You have led multi-quarter initiatives that required alignment across three or more engineering orgs.
  • Hands-on technical depth in Java or Kotlin, with practical knowledge of REST APIs, event-driven systems, and relational or key-value data stores. Comfortable in design reviews and code reviews. Willing to write production code when the team needs a tiebreaker.
  • Excellent written communication. You have written TDDs, post-mortems, and roadmap updates that senior leaders trusted without needing translation.
  • Bias for action: absorbs ambiguity and resolves it, escalates it upward when the situation warrants.

Nice to have

  • Experience building agentic workflows, internal AI tooling, or LLM-powered developer productivity systems.
  • Experience with OpenFGA, Zanzibar-style authorization, or graph platforms at scale.
  • Experience in regulated environments, ideally fintech, with exposure to SOX, PCI, or similar controls.
  • Familiarity with AWS, Kubernetes, Kafka, DynamoDB, and Temporal.
  • Prior work on multi-person or delegated access patterns (consumer & business banking, family accounts, custodial, trust relationships).

What the JD emphasized

  • Active, daily user of modern AI coding tools (Claude Code, Cursor, Copilot, or equivalent). Concrete examples of how you have used AI to accelerate your own output or your team's throughput.
  • Proven track record running a high traffic Tier-0 or equivalent critical platform: defined SLOs, owned on-call, led major incident reviews, and drove measurable reliability improvements.