AI Solutions Developer

The shape of it

In the posting’s own words

You'll be joining the Finance Operational Excellence team, reporting to the Head of Finance Operational Excellence. We are finance transformation and AI experts working side-by-side with Finance, Product, and Engineering teams to redefine processes and build the finance organization of the future. This is an opportunity for someone who enjoys working across disciplines: part solution developer, part data architect, part workflow designer, and part coach. You’ll have room to shape how applied AI is built and scaled both from a technical and end-user perspective.

What it asks for · 9

• 5+ years of experience in data analytics, technical operations, business intelligence, automation, solutions delivery, or a related field.
• Hands-on experience building AI-enabled tools, agents, automations, or workflows that changed a real business process—not solely using AI as a conversational tool.
• Strong SQL proficiency, including experience writing complex queries using CTEs, window functions, and joins for data analysis, transformation, or pipeline logic.
• A track record of independently scoping and delivering technical solutions for process improvement, demonstrating ownership from problem definition through adoption.
• Strong analytical and investigative skills, including the ability to identify root causes, debug complex data problems, and resolve inconsistencies.
• Strong written and verbal communication skills, with the ability to explain technical concepts to non-technical audiences and work effectively with domain experts and Engineering partners.
• Experience teaching, coaching, enabling users, or transferring ownership of a solution through documentation, training, or self-service tools.
• Working knowledge of development practices such as version control, testing, code review, and iterative delivery.
• Experience using low-code tools, scripting, workflow automation, AI-assisted development, or custom integrations, paired with curiosity and the ability to learn evolving technologies.

Also a plus

• Domain experience in Finance Operations, Financial Planning & Analysis (FP&A), Accounting, Treasury, Tax, Payments, or other areas.
• Familiarity with modern data tools and practices, such as Python, Databricks, ETL/ELT processes, data pipelines, and data-quality controls.
• Experience with Model Context Protocol or another extensibility or integration framework.
• Experience navigating financial systems and understanding how data flows through accounting, reporting, reconciliation, forecasting, or payments processes.
• Experience with change management, organizational transformation, or large-scale enablement programs.
• Experience building internal tools, templates, components, or playbooks that were adopted beyond the original team or use case.
• Experience working in a high-growth technology company with rapidly evolving processes and tools.

What the job covers

• Embed with Finance teams to diagnose workflows, identify high-leverage opportunities, and translate business, data, and control requirements into practical AI and automation solutions.
• Build and operationalize AI agents for Finance use cases, delivering end-to-end solutions from prototype through validation, monitoring, documentation, and handoff.
• Write and optimize SQL for data extraction, transformation, calculation, and validation, ensuring Finance-facing outputs are accurate, explainable, and reliable.
• Design reusable knowledge layers, evaluation methods, validation patterns, data-quality frameworks, and components that improve agent accuracy and accelerate future use cases.
• Identify agentic limitations and new possibilities; determine when to use existing capabilities, develop an alternative approach, or partner with Engineering to scope and test custom tools and integrations, including tools using Model Context Protocol where appropriate.
• Build alongside users, gather feedback through real deliverables, and iterate until the solution fits the workflow and earns user trust.
• Enable long-term ownership through clear SOPs, runbooks, training, and self-service tooling; coach Finance teams to operate, maintain, and evolve what has been built.
• Establish monitoring and observability for deployed agents, including metrics, alerting, and incident-response processes that support reliable operation.
• Diagnose technical and data issues, resolve problems independently where possible, and collaborate with Engineering when solutions require deeper platform changes.
• Measure adoption and impact, share lessons and wins, and turn successful implementations into standards, components, and playbooks for the broader Finance AI portfolio.

Tools and skills named

Words the posting leans on

• finance15×
• data13×
• solutions12×
• tools12×
• experience11×
• technical8×
• agents7×
• engineering7×
• workflow7×
• automation6×
• build6×
• processes6×
• requirements5×
• transformation5×
• building4×
• custom4×

Counted from the posting after the mission statement and the legal notices are set aside. The ones near the top are the ones a screener is looking for.

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