Role Summary

We are looking for a Technical Product Manager (TPM) to lead the delivery of AI Employees that run finance operations for enterprise customers.

This role sits at the intersection of Finance Transformation, Product, Technology, and Customer Delivery. You will work directly with customers to understand their business processes and challenges, translate those needs into clear product and technical requirements, and partner with Product, Engineering, FDE, QA, and Customer Success teams to deliver successful implementations.

The ideal candidate combines finance process depth with real technical fluency. You are comfortable working with customers, navigating ambiguity, driving execution, and translating business problems into technology solutions.

Technical knowledge matters in this role. You will work with APIs, integrations, data models, and agentic AI systems, so you should be able to hold a credible conversation with engineers and reason about how a solution is actually built.

Hands-on experience with agentic AI, LLM-based applications, or intelligent automation is a significant advantage. Deeper AI expertise can be built on the job, provided you bring finance process depth, client presence, structured thinking, and delivery ownership.

What You Will Do

1. Customer Discovery & Process Understanding

- Lead customer discovery sessions to understand business processes, requirements, pain points, and desired outcomes.
- Conduct process and product walkthroughs with business and technology stakeholders.
- Understand current-state and future-state processes, including exceptions, controls, dependencies, and operational challenges.
- Identify opportunities where AI, automation, and technology can improve existing finance processes.
- Drive requirement discussions and clarify business decisions with customers.

1. Product & Solution Definition

- Translate customer business problems into clear use cases, requirements, workflows, and acceptance criteria.
- Work closely with Product, Engineering, and FDE teams to convert business requirements into scalable technology solutions.
- Define where AI, deterministic automation, and human review each belong in a process, including exception handling and approval controls.
- Work through integration points, data flows, and system dependencies with customer IT and internal engineering teams.
- Participate in solution design discussions and help evaluate functional and technical trade-offs.
- Prioritize requirements based on customer value, business impact, feasibility, and delivery timelines.
- Contribute customer insights and feedback to product improvement and roadmap discussions.
- Help bridge the gap between business stakeholders and technical teams.

1. End-to-End Delivery

- Own customer projects from discovery through implementation, go-live, and closure.
- Create and maintain project plans, milestones, timelines, deliverables, and dependencies.
- Coordinate across Product, Engineering, FDE, QA, Customer Success, and customer teams.
- Track progress against agreed scope, timelines, and quality expectations.
- Ensure deliverables are completed and milestones are achieved as committed.
- Maintain project documentation, decisions, action items, and delivery status.

1. Risk, Issue & Dependency Management

- Proactively identify project risks, assumptions, issues, and dependencies.
- Maintain and manage the RAID log throughout the project lifecycle.
- Develop mitigation and resolution plans for delivery risks.
- Escalate blockers and critical decisions appropriately.
- Drive action items and dependencies to closure.




- Ensure risks are communicated proactively to customers and internal leadership.

1. Customer & Stakeholder Management

- Act as a key delivery and product-facing contact for customers.
- Independently lead customer meetings, discovery sessions, workshops, and project reviews.
- Communicate project progress, risks, decisions, dependencies, and timelines clearly.
- Manage customer expectations and proactively address concerns.
- Build strong relationships with business, finance, technology, and leadership stakeholders.
- Drive customer decisions, approvals, and milestone sign-offs.
- Work effectively with international customers and stakeholders across time zones.

1. Testing & Go-Live

- Coordinate business validation, UAT, and readiness activities with customers and internal teams.
- Define test scenarios for AI-driven steps, including accuracy expectations, exception paths, and human review checkpoints.
- Work with QA, Engineering, Product, and FDE teams to ensure solution readiness.
- Validate the go-live checklist and ensure all required approvals are secured.
- Coordinate production deployment and post-go-live stabilization.
- Support project closure and capture customer feedback and lessons learned.

What We Are Looking For
1. Finance Process & Domain Expertise

You should have hands-on understanding of one or more finance processes, such as:
- Accounts Payable (AP)
- Procure-to-Pay (P2P)
- Order-to-Cash (O2C)
- Record-to-Report (R2R)
- Financial Close
- Reconciliation
- FP&A;

You should be able to go beyond a high-level process map and understand how the process actually operates, including exceptions, dependencies, controls, handoffs, and operational challenges.
1. Technical Fluency

- Working understanding of how enterprise software is built and integrated: APIs, authentication, webhooks, data models, and file-based integrations.
- Ability to read structured data such as JSON or CSV and run basic SQL queries.
- Comfortable discussing solution architecture, system constraints, and technical trade-offs with engineers.
- Understanding of how AI is applied to enterprise processes, including where it performs reliably and what controls it requires.
- Ability to explain a technical design to a finance stakeholder and a finance control to an engineer.

1. Agentic AI Exposure (Strong Plus)

- Experience with agentic AI systems that execute multi-step work using tools and APIs, with retrieval, evaluation, and human review built in.
- Familiarity with prompt and context design, LLM evaluation, or agent orchestration frameworks.
- Exposure to GenAI, intelligent automation, RPA, or workflow automation in an enterprise setting.
- Awareness of AI governance topics such as audit trails, approval policies, data residency, and model risk.

1. Client-Facing Consulting Experience

- Experience working directly with customers or business stakeholders.
- Ability to conduct discovery sessions and process/product walkthroughs.
- Comfortable asking the right questions, challenging assumptions, and driving decisions.
- Ability to independently lead conversations with international customers.
- Robust executive and stakeholder communication skills.

1. Product Mindset

- Ability to take an ambiguous business problem and structure it into a clear use case.




- Ability to translate business needs into requirements and actionable deliverables.
- Comfortable working closely with Product, Engineering, and FDE teams.
- Strong understanding of the relationship between business processes, technology, and customer outcomes.
- An informed view of where AI and automation fit into enterprise finance processes and what they need to work reliably at scale.

1. Project & Stakeholder Management

- Experience managing projects, workstreams, dependencies, risks, and multiple stakeholders.
- Strong ownership of timelines and deliverables.
- Ability to operate effectively in a fast-paced and changing environment.
- Strong problem-solving and decision-making skills.
- Ability to drive execution without relying on formal authority.

Required Skills
- Finance process understanding
- Business analysis and requirement gathering
- Client discovery and stakeholder management
- Product thinking and solution definition
- Project and delivery management
- Risk and dependency management
- Software Development Life Cycle (SDLC)
- User stories and acceptance criteria
- APIs, integrations, and data flows
- Structured data (JSON, CSV) and basic SQL
- Working knowledge of AI and agentic AI concepts
- Jira, Azure DevOps, ClickUp, Asana, or similar tools
- Microsoft Excel and PowerPoint
- Excellent written and verbal communication

Good to Have
- Hands-on experience building or delivering agentic AI or LLM-based applications
- Experience implementing intelligent automation, RPA, or workflow automation
- Familiarity with MCP, A2A, or similar agent interoperability standards
- Experience in finance transformation or enterprise technology consulting
- Experience implementing SaaS or enterprise software
- Experience with ERP or finance platforms such as SAP, Oracle, NetSuite, Workday, or similar
- Experience working with Engineering, FDE, Product, or QA teams

You do not need to be an AI engineer. What matters is that you understand these systems well enough to design with them, question their output, and explain them to a finance leader. Qualifications & Experience

Required

- Bachelors or Master’s degree in Engineering, Computer Science, Information Technology, Finance, or Business, or a professional qualification such as CA or MBA.
- 3–6 years of relevant experience in Finance Transformation, Business Consulting, Technology Consulting, GBS Advisory, Enterprise Software Implementation, Finance Process Transformation, or Product/Technology Consulting.
- Hands-on experience with at least one core finance process such as AP, P2P, O2C, R2R, Close/Reconciliation, or FP&A.;
- Working technical knowledge of APIs, integrations, data structures, and the software delivery lifecycle.

Preferred
- Bachelor’s or Master’s degree in Computer Science, Information Technology, or Computer Engineering.
- Finance certification courses such as CA, CPA, CMA, CFA, ACCA, or CIMA.
- Coursework or certification in AI, machine learning, or agentic AI systems.
- Practical experience delivering AI or automation projects in a finance or enterprise environment.
- PMP, PRINCE2, CSM, or Agile certification.

Why This Role?
- Work directly with global customers on complex finance transformation problems.
- Help translate real-world finance processes into AI Employees that run them end to end.
- Work hands-on with agentic AI systems running in production.
- Partner closely with Product and Engineering teams.
- Influence product and solution decisions based on customer needs.
- Own projects from discovery through successful implementation and go-live.
- Develop into a strong product and technology leader while building on your finance and consulting expertise.

📌 Technical Product Manager Finance Transformation AI (Gurugram)
🏢 Supervity
📍 Gurugram