Finance Analytics & AI Manager

We need to output HTML fragment with sections: About the role? The posting includes description of work, responsibilities, qualifications, skills, maybe benefits? There's no explicit pay, schedule, benefits. There's a line about travel 50% and limited immigration sponsorship. That could be part of "Requirements" or "Qualifications". We should not create sections without real content. So we can have sections: About the role (maybe intro paragraph), Responsibilities (list of duties), Qualifications (required and preferred), Skills (list of skills). Also maybe "Travel" could be part of Qualifications? But we can include a short paragraph under Qualifications about travel and sponsorship. We must not repeat job title as heading. No Job ID. Remove boilerplate like recruiting ends date? That's metadata; we can fold into short p or drop. The instruction: "Do NOT put Job ID / requisition numbers as headings — fold minor metadata into a short

or drop it." So we can include a short p with "Recruiting for this role ends on 12/01/2026". Probably keep it. We must not include EEO etc. Not present. We need to preserve all substantive information. So we need to include all responsibilities bullet points, qualifications required, preferred, skills list. We must use

for section headings. Use

• for any list of duties/requirements/benefits, and

  for prose. We must not create sections like Pay, Schedule, Benefits unless posting actually states them. Not present. Thus sections: About the role (intro paragraph), Responsibilities, Qualifications, Skills. We could also have a "Travel and Sponsorship" but that's minor metadata; could be part of Qualifications as a paragraph. Let's extract content. Intro paragraph: "In an increasingly challenging environment marked by disruptive tech like AI, market uncertainty, and regulatory change, finance and global business services leaders recognize the opportunity to better serve the enterprise, shareholders, customers, and regulators. Deloitte helps navigate this complexity by bringing deep industry insights and integrated solutions to achieve business objectives. From strategy to technology to operations, and across workforce, risk, assurance, and tax, Deloitte helps drive value along the Finance Transformation journey." Then maybe a short p for recruiting end date. Then responsibilities: list of bullet points under "Work you'll do". Let's capture each sentence. From "Work you'll do As a Finance Analytics & AI Manager on the Finance Transformation team, you'll work with the best in the business to solve the toughest client problems. From learning to leadership, this is your chance to take your career to the next level. Our Managers are expected to contribute to the firm's growth and development in a variety of ways." Then list: - Lead AI solution development and deployment, managing day-to-day client relationships, and ensuring quality, performance, and technical outcomes meet client expectations - Serve as a techno-functional bridge between client stakeholders and technical delivery teams - clarifying requirements, resolving design ambiguities, and providing solution guidance - Lead small engagements or workstreams within larger programs that identify, design, and implement AI-enabled business and technology solutions for large enterprises - Partner with developers and technical teams to translate design requirements into build specifications, providing functional guidance throughout development, testing, and deployment - Translate client business needs and finance process requirements into clear AI-related functional and technical design requirements, ensuring solutions are both technically sound and aligned to business outcomes - Engage clients to identify business issues and high-impact AI use cases, shaping hypotheses, value cases, and solution design requirements - Perform assessments using quantitative and qualitative techniques, including AI-enabled diagnostics and discovery methods, to inform solution architecture and design decisions - Define scope, objectives, requirements, and delivery plans; managing solution architecture planning through execution, delivery, and post-implementation review - Contributing to business development by supporting proposals, RFP responses, and orals, and by mentoring and developing team members We need to ensure each bullet is

• . Then skills: list under "A successful candidate would possess these skills:" bullet list. - Ability to work independently and collaborate as part of a team - Effective written and verbal communication skills - Meticulous attention to detail and quality of work product - Ability to build and sustain professional relationships - Ability to lead projects or workstreams - Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment - Strong interpersonal skills and professional demeanor - Ability to meet deadlines - Ability to mentor and provide clear guidance to others Qualifications Required: list. - Bachelor's degree in Engineering, Computer Science, a related field, or equivalent practical experience. - 6+ years of experience with software development using Python or similar coding languages. - Experience architecting AI systems on cloud platforms (e.g., GCP). - Experience taking production-grade AI-driven solutions from conception to launch for customers. - Experience leading technical discovery sessions with customers. - Experience building pipelines for structured and unstructured data using both vector databases and retrieval-augmented generation (RAG)-like architectures to power enterprise AI solutions. - Experience using Python and Structured Query Language (SQL) to develop analytics, machine learning, data engineering, or automation solutions in Amazon Web Services (AWS), Google Cloud Platform (GCP), or Microsoft Azure environments - Experience architecting generative and agentic AI solutions across infrastructure, model, and application layers, including one or more of the following infrastructure platforms: NVIDIA, Amazon Web Services (AWS), Google Cloud Platform (GCP), or Microsoft Azure; one or more of the following model platforms: GPT-4o, Claude, or Llama; and one or more of the following application platforms: ChatGPT, Claude, or Gemini - Experience working with finance data and use cases related to planning, budgeting, forecasting, close, profitability, or cost allocations - Ability to travel 50%, on average, based on the work you do and the clients and industries/sectors you serve. - Limited immigration sponsorship may be available. Preferred: list. - Master's degree in Computer Science, Data Science, Analytics, Finance, Mathematics, or Statistics - Experience implementing multi-agent systems using frameworks (e.g., LangGraph, CrewAI, ADK) and patterns (e.g., ReAct, self-reflection, hierarchical delegation). - Knowledge of LLM-native metrics (e.g., tokens/sec, cost-per-request) and techniques for optimizing state management and granular tracing. - Experience with finance platforms such as SAP, Oracle, Anaplan, OneStream, or Workday - One or more certifications in artificial intelligence, machine learning, Amazon Web Services, Microsoft Azure, or Google Cloud Platform, Snowflake, Databricks - 2+ years of experience supporting pre-sales, proposals, RFP responses, and mentoring data and AI delivery teams We could combine Required and Preferred under Qualifications section with subheadings? But we only have h3 for section headings; we could have a Qualifications section and inside we can have paragraphs and lists. Could separate Required and Preferred as

  Required:

  then list. But we must not invent headings; we can use

  for prose. So we can have a

  with "Required:" then

  . Similarly for Preferred. Now About the role: we can have a paragraph with the intro text. We also have a short p for recruiting end date. We must not repeat job title as heading. Not needed. Now produce HTML fragment. Let's craft:

  About the role

  In an increasingly challenging environment marked by disruptive tech like AI, market uncertainty, and regulatory change, finance and global business services leaders recognize the opportunity to better serve the enterprise, shareholders, customers, and regulators. Deloitte helps navigate this complexity by bringing deep industry insights and integrated solutions to achieve business objectives. From strategy to technology to operations, and across workforce, risk, assurance, and tax, Deloitte helps drive value along the Finance Transformation journey.

  Recruiting for this role ends on 12/01/2026.

  Responsibilities

  • Lead AI solution development and deployment, managing day-to-day client relationships, and ensuring quality, performance, and technical outcomes meet client expectations
  • Serve as a techno-functional bridge between client stakeholders and technical delivery teams - clarifying requirements, resolving design ambiguities, and providing solution guidance
  • Lead small engagements or workstreams within larger programs that identify, design, and implement AI-enabled business and technology solutions for large enterprises
  • Partner with developers and technical teams to translate design requirements into build specifications, providing functional guidance throughout development, testing, and deployment
  • Translate client business needs and finance process requirements into clear AI-related functional and technical design requirements, ensuring solutions are both technically sound and aligned to business outcomes
  • Engage clients to identify business issues and high-impact AI use cases, shaping hypotheses, value cases, and solution design requirements
  • Perform assessments using quantitative and qualitative techniques, including AI-enabled diagnostics and discovery methods, to inform solution architecture and design decisions
  • Define scope, objectives, requirements, and delivery plans; managing solution architecture planning through execution, delivery, and post-implementation review
  • Contributing to business development by supporting proposals, RFP responses, and orals, and by mentoring and developing team members

  Qualifications

  Required:

  • Bachelor's degree in Engineering, Computer Science, a related field, or equivalent practical experience.
  • 6+ years of experience with software development using Python or similar coding languages.
  • Experience architecting AI systems on cloud platforms (e.g., GCP).
  • Experience taking production-grade AI-driven solutions from conception to launch for customers.
  • Experience leading technical discovery sessions with customers.
  • Experience building pipelines for structured and unstructured data using both vector databases and retrieval-augmented generation (RAG)-like architectures to power enterprise AI solutions.
  • Experience using Python and Structured Query Language (SQL) to develop analytics, machine learning, data engineering, or automation solutions in Amazon Web Services (AWS), Google Cloud Platform (GCP), or Microsoft Azure environments
  • Experience architecting generative and agentic AI solutions across infrastructure, model, and application layers, including one or more of the following infrastructure platforms: NVIDIA, Amazon Web Services (AWS), Google Cloud Platform (GCP), or Microsoft Azure; one or more of the following model platforms: GPT-4o, Claude, or Llama; and one or more of the following application platforms: ChatGPT, Claude, or Gemini
  • Experience working with finance data and use cases related to planning, budgeting, forecasting, close, profitability, or cost allocations
  • Ability to travel 50%, on average, based on the work you do and the clients and industries/sectors you serve.
  • Limited immigration sponsorship may be available.

  Preferred:

  • Master's degree in Computer Science, Data Science, Analytics, Finance, Mathematics, or Statistics
  • Experience implementing multi-agent systems using frameworks (e.g., LangGraph, CrewAI, ADK) and patterns (e.g., ReAct, self-reflection, hierarchical delegation).
  • Knowledge of LLM-native metrics (e.g., tokens/sec, cost-per-request) and techniques for optimizing state management and granular tracing.
  • Experience with finance platforms such as SAP, Oracle, Anaplan, OneStream, or Workday
  • One or more certifications in artificial intelligence, machine learning, Amazon Web Services, Microsoft Azure, or Google Cloud Platform, Snowflake, Databricks
  • 2+ years of experience supporting pre-sales, proposals, RFP responses, and mentoring data and AI delivery teams

  Skills

  • Ability to work independently and collaborate as