Staff Software Engineer, AI Developer Experience
SoFi is hiring a Staff Software Engineer, AI Developer Experience in San Francisco and Seattle, United States. Level rates it ; you can apply on SoFi.
Level's read on this job
- Level rates this software engineer role Works on AI ●●●○: the daily work is on AI products, without building the model.
- Tools and skills the posting cites include prompt engineering, AI agents and AI evaluation.
- Level classifies it as a lead role.
- Level lists 62 other open roles at SoFi.
- The role was posted in the last few days.
AI in this role
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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:
SoFi's AI Platform team builds the foundation that enables every engineer at SoFi to ship faster, safer, and with higher leverage from AI. Our AI Developer Experience (AI DevEx) team owns SoFi's interactive coding strategy and underlying infrastructure: AI economics, coding harnesses and harness vending, our evaluation platform, the enterprise AI Gateway, and intelligent model routing.
As a founding Staff Software Engineer, you'll be a technical leader on the team: owning major platform systems, setting the team's engineering standards, and working closely with our Autonomous Coding, CI/CD, and Code Factory teams and the engineering teams we serve.
What you’ll do:
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Own platform systems end-to-end: design, build, and operate foundational components of the AI Gateway, model routing, eval platform, and harness vending, transforming broadly defined challenges into production-grade systems.
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Instrument AI economics: develop usage telemetry, cost allocation, and chargeback mechanisms that provide transparent visibility into AI spend per developer.
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Lead team execution: plan feature architecture and implementation paths, parallelize work streams across teammates, and align cross-team dependencies with product and engineering leaders.
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Guide technical design: facilitate design reviews, evaluate architectural trade-offs, and align critical technical outcomes with the broader SoFi engineering community.
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Establish technical standards: define coding conventions, automated patterns, and architectural standards that result in maintainable, extensible software for other engineers.
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Drive operational excellence: automate build, test, and deployment workflows; serve as a leading resolver on production incidents; and resolve root causes through post-incident actions.
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Maintain a 6-to-12-month technical vision: anticipate system growth, prioritize architectural hygiene, and make pragmatic build-versus-adopt choices across an evolving tooling ecosystem.
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Partner with internal engineering teams: engage directly with developers as primary customers to understand their workflows, drive adoption of interactive coding tools, and translate feedback into continuous system enhancements.
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Mentor and develop engineers: provide well-calibrated, constructive code and design feedback to accelerate team member growth.
What you’ll need:
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Education & Minimum Experience Requirements: Bachelor’s Degree + 3–4 Years of Experience OR Master’s Degree + 2–3 Years of Experience in software engineering, computer science, or a related field.
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Advanced programming expertise in at least one modern backend language (such as Java, Kotlin, Python, Go, or Scala).
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Proven distributed systems expertise with sound judgment evaluating trade-offs across security, concurrency, fault tolerance, horizontal scaling, and idempotence.
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Track record of technical leadership guiding feature delivery, cross-functional alignment, and architecture on production platforms.
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Hands-on experience developing with or building AI-assisted developer tooling and LLM-based systems (e.g., coding assistants, autonomous agents, prompt engineering, and tool execution frameworks).
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Hands-on experience with cloud infrastructure (AWS/GCP), containerization, modern CI/CD pipelines, and operational on-call service ownership.
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Product-oriented engineering mindset: commitment to treating internal developers as customers and measuring success through platform adoption and user sentiment.
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Clear written and verbal communication skills, including the ability to draft structured technical design documents and present options to diverse stakeholders.
AI-Assisted Engineering Expectations:
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Apply AI tools responsibly to prototype solutions, navigate unfamiliar codebases, and accelerate implementation velocity while upholding high security and safety standards.
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Critically inspect and validate AI-generated code, backing all implementations with comprehensive automated tests to ensure long-term maintainability.
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Maintain rigorous compliance with data governance and security policies, ensuring sensitive member data and proprietary assets are never exposed to unapproved tools.
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Elevate team productivity by establishing and sharing proven harnesses, prompt templates, and operational guardrails.
Nice to have:
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Direct experience building or operating LLM evaluation pipelines, model proxies, or semantic request routing layers.
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Experience engineering internal developer platforms (IDP), developer tooling, or CLI workflows.
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Experience with cost telemetry, usage-based metering, or FinOps instrumentation.
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Background in fintech or adjacent environments operating under strict data compliance and security regulations.
How we rate this
Staff Software Engineer, AI Developer Experience at SoFi rates 68 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in software engineer jobs at this level
Pay
- Typical software engineer job
- $167k
This posting doesn't list pay. Use the typical software engineer figure when pay comes up. See software engineer jobs
Questions you could be asked
- How do you structure and test a prompt to get consistent output from a language model?
- How do you decide when an AI agent can act on its own versus asking for approval first?
- How do you decide that one model's output is better than another's for a given task?
- Describe a typical day in a role like this one: which parts run through AI directly?
- If you removed AI from this role, what would be left, and how do you decide what still needs a human?
Adapt your resume
- List these exact terms on your resume: Prompt engineering, AI agents, and AI Evaluation. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
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