Associate AI Engineer, Finance Transformation

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Who we are:

The role:

SoFis Associate AI Engineer Finance Transformation is a hands-on builder within SoFis Finance organization focused on building agentic AI workflows that transform how Finance works from close and reconciliations to forecasting and reporting.

Finance has one of the largest AI opportunity surfaces at SoFi: over a hundred identified use cases an active champions network and executive this role you will build multi-step AI workflows on approved enterprise AI platforms stand up the telemetry that measures AI usage cost and ROI across Finance and help make AI outputs trustworthy enough for Finance decision-making in a controlled environment where outputs must be explainable auditable and reconciled to the number.

You will work directly with the AI Transformation Manager for Finance who owns use-case strategy and stakeholder engagement and in close partnership with SoFis AI SDLC and platform teams who support the path from prototype to production. This is a build-focused role with an unusual growth surface: SoFis AI Engineering ladder (through Staff and Senior Staff) is the visible progression path.

What youll do:

• Build agentic AI workflows: Develop multi-step AI workflows such as planning tool use retrieval structured orchestration on approved enterprise AI platforms and agentic coding tools to automate Finance processes.
• Build AI telemetry: Own usage cost engagement and ROI reporting across Finance AI tools from source extraction to dashboards leadership relies on.
• Contribute to the experience layer: Help design how Finance users interact with AI systems including workflows interfaces and feedback loops that build trust and adoption.
• Validate outputs: Apply and refine repeatable patterns for validating AI outputs before they inform Finance decisions such as reconciliation documented assumptions human-in-the-loop checkpoints.
• Prototype fast: Turn prioritized Finance use cases into working prototypes then partner with AI SDLC and platform engineering on the path to production.
• Learn the domain: Develop Finance fluency (close reconciliation reporting workflows) and SQL rigor in seat with structured support.

What youll need:

• Bachelors or Masters degree in Computer Science Data Science AI/ML or a related field or equivalent practical experience.
• 13 years of experience building with LLMs or an exceptional new-grad record with substantial hands-on agent projects (academic personal open-source or internship work all count).
• Demonstrated hands-on experience with LLM APIs prompt engineering RAG or agent frameworks with a portfolio of projects where you can clearly explain what you personally designed and why.
• Working Python for automation API integration and prototyping.
• Basic SQL for querying data (Finance-grade rigor will be developed in seat).
• Builder mindset: bias toward making a working thing rather than describing one.
• Willingness to learn Finance domain context and communicate with non-technical stakeholders with support.

Nice to have:

• Exposure to evaluation tracing or observability practices for AI systems.
• Exposure to Snowflake Cortex or natural-language-to-SQL tooling.
• Exposure to Finance Accounting or another controlled/regulated data environment.
• Experience building user-facing tools or internal apps powered by AI.