SoFi
Finance / FinServ
StaffAIEngineer
Neural analysis suggests this role is
optimal for Staff candidates.
“Staff AI Engineer at SoFi. Skills: Agentic AI systems, LLMs, System design, Productionizing AI systems, Context engineering. Owning the design, development, and evolution of agentic AI systems. Architecting, building, and scaling AI systems”
What You'll Achieve.
Measurable impact; Enhance risk management and internal workflows; Create reliable, reusable, and production-grade solutions; Ensure AI systems are intuitive, reliable, and effective in high-stakes risk environments; Deliver measurable outcomes
Industry & Context.
Translate complex, ambiguous problems into scalable, production-grade AI systems; Ability to operate effectively in ambiguous problem spaces and translate them into well-defined systems
What They're Looking For.
Must Have
Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, or a related field, 7+ years of software engineering experience, significant experience building and scaling AI-powered systems in production, experience working with LLMs and building applications using prompting, APIs, and/or agent frameworks, Experience designing and implementing agentic systems, including patterns such as tool use, multi-step reasoning, and workflow orchestration, Deep experience in context engineering for LLM systems, including structuring inputs and outputs, prompt design, and retrieval-based approaches, backend engineering experience, including building scalable services and APIs (Python preferred), Experience designing systems on cloud platforms such as AWS, Azure, or GCP, with an understanding of modern development and deployment practices, Experience working with structured and unstructured data, including building pipelines to support downstream AI applications, Experience defining and implementing evaluation frameworks for AI systems, including metrics, experimentation, and performance iteration, system design skills, with the ability to architect scalable, reliable solutions, Ability to operate effectively in ambiguous problem spaces and translate them into well-defined systems
Nice to Have
Experience designing and building user-facing workflows or internal tools powered by AI, Familiarity with observability and evaluation tools for AI systems such as Langfuse, LangSmith, or similar, Experience working in financial services or building systems for risk-related use cases, Experience with frontend technologies such as React for building AI-powered interfaces, Experience contributing to shared platforms, libraries, or internal tooling that enable reuse across teams, Experience building systems that require explainability, auditability, or operate in regulated environments
What You'll Do.
and evolution of agentic AI systems
and scaling AI systems
and production-grade solutions
Operating at the intersection of the intelligence layer and the experience layer
Shaping how AI systems are designed and integrated into critical workflows
ambiguous problems into scalable
production-grade AI systems
Leading the design and development of AI systems that leverage multi-step reasoning
and structured workflows
Incorporating planning
and adaptive control flow
and feedback loops for AI systems
Defining and implementing approaches for structuring inputs
Developing production-grade services and APIs
Integrating agents into real systems
and maintainability of AI systems
and evaluation frameworks
Identifying high-impact opportunities to apply AI
Rapidly prototyping solutions
Evaluating emerging tools and approaches
How You'll Work.
Team & Collaboration
Partner with risk, engineering, and business teams; Close coordination with users / stakeholders; Cross-Functional Collaboration; Contribute to shared platforms, libraries, or internal tooling
Communication Scope
Communication and collaboration skills; Ability to work cross-functionally and influence technical decisions
Process & Methodology
Translating complex, ambiguous problems into scalable, production-grade AI systems with measurable impact, Ability to operate effectively in ambiguous problem spaces and translate them into well-defined systems, Demonstrated ownership mindset, with a track record of delivering high-impact systems end-to-end
Full Job Description
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: SoFi’s Staff AI Engineer is a highly experienced, hands-on individual contributor within SoFi’s growing independent risk organization, focused on owning the design, development, and evolution of agentic AI systems to solve real-world, high-impact problems. This role will be instrumental in architecting, building, and scaling AI systems that enhance risk management and internal workflows, with a focus on creating reliable, reusable, and production-grade solutions. This role operates at the intersection of the intelligence layer, including LLMs, agents, and orchestration, and the experience layer, which defines how users interact with and derive value from AI systems. You will shape how these systems are designed and integrated into critical workflows, ensuring they are intuitive, reliable, and effective in high-stakes risk environments. You will work closely with the Senior Manager of AI Engineering as well as business stakeholders, to translate complex, ambiguous problems into scalable, production-grade AI systems with measurable impact. What you’ll do: Architect and Develop Agentic AI Systems: Lead the design and development of AI systems that leverage multi-step reasoning, tool use, and structured workflows, using frameworks such as LangGraph or similar approaches. Incorporate planning, memory,
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