Software Engineer, Streaming and Workflows

Employee Applicant Privacy Notice

Who we are:

Shape a brighter financial future with us.

Together with our members, we’re changing the way people think about and interact with personal finance.

We’re a next-generation financial services company and national bank using innovative, mobile-first technology to help our millions of members reach their goals. The industry is going through an unprecedented transformation, and we’re at the forefront. We’re proud to come to work every day knowing that what we do has a direct impact on people’s lives, with our core values guiding us every step of the way. Join us to invest in yourself, your career, and the financial world.

The role:

As a Software Engineer (IC2) on the Streaming & Workflows (SAW) team at SoFi, you will be embedded in one of the most critical platform initiatives across the company: the ground-up, greenfield rebuild of our enterprise File Automation Platform. This mission-critical platform coordinates all external file transfers moving millions to billions of dollars between SoFi and major financial institutions, including clearing banks and regulatory reporting to the Federal Reserve.

In this role, you will partner closely with other engineers based in Seattle to build a modern, multi-region, resilient distributed file orchestration engine. You will pair solid backend engineering execution with systems thinking, contributing to feature development, automated testing, and operational health while leveraging AI-assisted development tools responsibly to accelerate delivery.

What you’ll do:

• Build and ship core features for the net-new multi-region File Automation Platform, replacing legacy file transfer infrastructure with scalable, secure microservices.
• Own a defined component or service slice end-to-end (e.g., protocol adapters, AWS Transfer Family/SFTP integrations, file validation, ingestion pipelines, and audit logging).
• Write modular, tested, and maintainable backend code in Java, Kotlin, Go, or Python using established distributed patterns.
• Partner closely with senior teammates in Seattle during design discussions to clarify requirements, define API boundaries, and implement edge-case handling.
• Build with evidence: implement automated unit, integration, and contract tests, along with metrics, structured logging, and Datadog dashboards to ensure high operational observability.
• Participate in code reviews, giving and receiving constructive peer feedback to raise software quality.
• Join the operational on-call rotation: verify production changes carefully, diagnose common runtime failures using disciplined debugging practices, and apply staged, low-risk fixes.
• Collaborate with internal application teams across Lending, Banking, Invest, and Credit Card to ensure smooth integration with platform tools.

What you’ll need:

• Education & Minimum Experience Requirements: Bachelor’s Degree + 2 Years of Experience building and maintaining backend services or distributed systems in production or Master’s Degree in Computer Science, Software Engineering, or a related technical field without industry experience.
• Proficiency in at least one modern programming language: Java, Kotlin, Go, or Python.
• Familiarity with cloud infrastructure (AWS preferred, Azure or GCP acceptable), containers (Docker), and Kubernetes.
• Experience with modern software delivery workflows: git, CI/CD pipelines, Infrastructure as Code (Terraform), and telemetry/observability tooling (e.g., Datadog, Prometheus).
• Demonstrated commitment to operational ownership, attention to detail, and a team-first mindset.

AI-Assisted Engineering Expectations:

• Apply AI-assisted development tools responsibly on a daily basis to accelerate prototyping, generate unit/integration test suites, draft documentation, and assist in incident debugging while safeguarding sensitive financial data.
• Critically review and validate AI-generated code to ensure correctness, reliability, security, and long-term maintainability.

Nice to have:

• Prior experience working on an infrastructure, platform, or developer-enablement team supporting internal engineering users.
• Familiarity with file transfer systems (AWS Transfer Family, SFTP, FTPS), secure protocol integrations, or enterprise job automation.
• Exposure to distributed workflow engines (Temporal, Cadence) or event-streaming architectures (Apache Kafka, WarpStream).
• Basic exposure to financial services, banking operations, or regulated data handling.