Finance AI Manager

Deloitte Deloitte · Consulting

Manager role focused on leading engagements to identify, design, and implement AI-enabled business and technology solutions for large enterprises, specifically within the finance function. This involves client engagement, use case identification, solution development, deployment, and contributing to business development. The role emphasizes generative AI solutions across the technology stack and requires experience with cloud platforms and end-to-end AI deliveries in finance domains.

What you'd actually do

  1. You will lead small engagements or workstreams within larger programs that identify, design, and implement AI-enabled business and technology solutions for large enterprises.
  2. You will engage clients to identify business issues and high-impact AI use cases, shaping hypotheses and value cases.
  3. You will perform assessments using quantitative and qualitative techniques, including AI-enabled diagnostics and discovery methods.
  4. You will define scope, objectives, requirements, and delivery plans; manage solution architecture planning through execution, delivery, and post-implementation review.
  5. You will oversee AI solution development and deployment, manage day-to-day client relationships, and ensure quality and performance outcomes.

Skills

Required

  • 7+ years of experience in consulting (professional services) or industry architecting and deploying artificial intelligence solutions and other technical solutions.
  • Bachelor’s degree in Business, Computer Science, Data Science, or a closely defined field from an accredited institution.
  • 3+ years designing and delivering generative AI solutions across the technology stack, including infrastructure (e.g., AWS, Azure, GCP), model layer (e.g., GPT-4o, Claude, Llama), and application layer (e.g., ChatGPT, Claude, Gemini).
  • 3+ years building solutions on cloud platforms (AWS, Azure, or GCP).
  • 3+ end-to-end AI solution deliveries (proofs of concept and/or scaled solutions) demonstrating business value in finance domains such as FP&A, controllership (close and consolidation), tax, treasury, management reporting, or external reporting.
  • 2+ years defining product roadmaps and prioritizing features with cross-functional teams (e.g., data science, engineering, finance).
  • Ability to travel 25–50%, on average, based on the work you do and the clients and industries/sectors you serve.

Nice to have

  • Bachelor’s degree from a STEM-designated program; master’s degree preferred.
  • One or more AI/ML certifications (e.g., AWS, Azure, Google).
  • 2+ years defining and prioritizing generative AI use cases using quantitative value frameworks.
  • 2+ years integrating applications and services via APIs.
  • 1+ year applying responsible AI practices for model training, evaluation, and deployment.
  • 2+ years in finance transformation, accounting, ERP/EPM implementation, data management/analytics, or project management.
  • 1+ proof of concept using agentic AI for end-to-end process automation.
  • Experience defining and tracking KPIs and success metrics for generative or predictive AI solutions.
  • Experience creating technical documentation and user guides for AI solutions.
  • Experience with pre-sales activities, proposals, and RFP responses.
  • Proficiency with Microsoft Word, Excel, PowerPoint, Outlook, and Teams.
  • Experience mentoring or coaching junior practitioners.

What the JD emphasized

  • architecting and deploying artificial intelligence solutions
  • designing and delivering generative AI solutions
  • end-to-end AI solution deliveries
  • proof of concept using agentic AI for end-to-end process automation

Other signals

  • AI-enabled business and technology solutions
  • AI use cases
  • AI-enabled diagnostics
  • AI solution development and deployment
  • Finance AI team focuses on automating, accelerating, and augmenting the finance function through data and AI models
  • advising, implementing, and operating innovative AI solutions
  • architecting and deploying artificial intelligence solutions
  • designing and delivering generative AI solutions
  • end-to-end AI solution deliveries
  • defining product roadmaps and prioritizing features with cross-functional teams
  • defining and prioritizing generative AI use cases
  • integrating applications and services via APIs
  • applying responsible AI practices for model training, evaluation, and deployment
  • proof of concept using agentic AI for end-to-end process automation
  • defining and tracking KPIs and success metrics for generative or predictive AI solutions
  • creating technical documentation and user guides for AI solutions