Sr Staff Forward Deployed Engineer, Enterprise AI
SoFi · Seattle, United States +1 · 12d ago
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Who we are:
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The Role
SoFi is building an internal AI platform that will change how employees across the company work. It combines models, enterprise context, tools, memory, governed capabilities, and an extensible agent harness so teams can move beyond chat and apply AI to meaningful business workflows.
You will work with the AI Platform engineering team, product leader, and subject-matter experts across the company. You will help departments reimagine how their work gets done, build the first workflows that make that future real, and turn what you learn in the field into durable platform capabilities.
Because you will be the first person in this role, you will also define what forward deployment means at SoFi: how we discover opportunities, onboard departments, build and evaluate workflows, measure outcomes, support users, and translate repeated needs into platform investments. Your work will establish the technical and operating foundation for a broader AI enablement capability.
This role does not have a playbook. It is an opportunity to write one and to define how applied AI changes the way work gets done across SoFi. This is a rare opportunity to shape both an enterprise AI platform and the organization that brings it to life.
What You’ll Do
- You will operate as a product-minded engineer, platform architect, and hands-on builder. One week you may be mapping a complex Finance workflow with domain experts; the next, prototyping an agentic solution, defining its evaluations, and contributing a new capability to the shared platform.
- Partner with leaders and subject-matter experts across SoFi to identify high-value opportunities to transform work with AI.
- Embed with internal departments to understand their workflows, systems, data, constraints, and measures of success and deploy AI-enabled workflows that solve real business problems.
- Lead departments from initial discovery through onboarding, adoption, production use, and measurable outcomes.
- Develop the playbooks, technical patterns, and operating practices that allow AI enablement to scale across the company.
- Build reusable skills, tools, integrations, agents, and workflow components on top of SoFi's internal AI platform.
- Contribute directly to the platform when field deployments reveal missing capabilities or opportunities to improve the developer and user experience.
- Create tight feedback loops among users, AI Enablement, product, and platform engineering.
- Serve as a trusted technical advisor to senior business and technology leaders navigating the opportunities and tradeoffs of applied AI.
What You’ll Need
- Deep experience building and operating sophisticated software systems at Sr Staff Engineer equivalent scope.
- A track record of leading technically ambiguous, cross-functional initiatives from problem definition through production adoption.
- Strong product judgment and an instinct for finding the real problem behind a feature request.
- Experience designing applications, platforms, developer tools, workflow systems, or distributed systems.
- Practical experience building with large language models, including tool use, context engineering, agents, evaluations, and human-in-the-loop patterns.
- The judgment to distinguish among a prototype, a department-specific solution, and a capability that belongs in a shared platform.
- Exceptional written and verbal communication skills across technical and nontechnical audiences.
- Comfort creating structure, standards, and momentum in a space where the operating model is still being formed.
Nice to Have
- Experience as a founding or early Forward Deployed Engineer, product engineer, product manager, solutions architect, or technical leader for an enterprise platform.
- Experience building an internal developer platform, AI platform, enterprise productivity product, or agentic system.
- Experience building evaluation and feedback systems for nondeterministic or AI-enabled products.
- Experience operating in financial services or another highly regulated environment.
What Success Looks Like:
- Established a repeatable model for taking departments from opportunity discovery to successful production use.
- Delivered AI-enabled workflows that create measurable improvements in speed, quality, capacity, or employee experience.
- Built a trusted partnership among internal users, AI Enablement, and the AI Platform organization.
- Converted insights from early deployments into reusable capabilities within the shared platform.
- Defined standards for onboarding, workflow development, evaluation, deployment, support, and continuous improvement.
- Created the technical and operating foundation from which SoFi can scale its Forward Deployed Engineering and AI Enablement capabilities.