Associate AI Engineer, Finance Transformation

About This RoleAI processing…

Key Responsibilities

• 1
  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.
• 2
  Build AI telemetry: Own usage, cost, engagement, and ROI reporting across Finance AI tools, from source extraction to dashboards leadership relies on.
• 3
  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.
• 4
  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.
• 5
  Prototype fast: Turn prioritized Finance use cases into working prototypes, then partner with AI SDLC and platform engineering on the path to production.
• 6
  Learn the domain: Develop Finance fluency (close, reconciliation, reporting workflows) and SQL rigor in seat, with structured support.

Requirements

• Bachelor's or Master's degree in Computer Science, Data Science, AI/ML, or a related field, or equivalent practical experience.
• 1–3 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.

Perks & Benefits