Synced from Greenhouse · Aug 11

AI Deployment Lead

ProdigalMumbaiPosted Aug 11, 2026
Technical Program ManagerMid
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Aug 11
Posted
Greenhouse
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Job descriptionReq 5066143007

About Prodigal

Prodigal is the connected AI platform leading financial institutions use to run their operations.

We work with banks, lenders, credit unions, and other financial companies that lend money to people and manage those relationships over time.

These institutions make millions of high-stakes decisions every day. Who should they reach? When should they reach them? What should they say or offer? When should a case move to a human? How should that change based on the borrower, the account, previous interactions, and the regulations involved?

Getting those decisions right requires a deep understanding of the people, processes, rules, and edge cases behind them.

Prodigal has spent the last eight years building that understanding. More than a billion interactions between financial institutions and their customers have shaped the intelligence, guardrails, and AI agents we now run in production across North America.

Today, our AI agents analyze conversations, capture context, guide human agents, decide the next action, conduct customer conversations, orchestrate outreach, and help people complete payments and resolutions. They are connected, so what is learned in one interaction can inform what happens next.

We are expanding this swarm of AI agents across more of the work financial institutions do: originations, document processing, back-office workflows, servicing, and other critical operations where money, identity, people, and regulation intersect.

We are backed by Y Combinator, Accel, and Menlo Ventures, and work with 100+ financial institutions across North America. Listen directly from our CTO, Cofounder - Sangram Raje

The Role

This is one of the most critical and demanding roles at Prodigal.

As an AI Deployment Lead, you are the person who takes an AI agent from a signed contract to a live, performing system and then keeps it getting better. You sit at the intersection of customer understanding, technical depth, and operational rigor. You own the outcome.

You will work directly with our North American customers - debt collection agencies, lenders, and loan servicers, to understand how their businesses actually run: their call flows, agent scripts/talk-tracks, compliance constraints, telephony/ dialer infrastructure, payment gateways, CRM systems, and APIs. You will translate that understanding into precise requirements and make sure what gets built is right before it ever touches a live call in production.

This is not a project management role with a technical veneer. You will design how the agent should think, speak, and behave across every scenario, validate that it does, and push for refinements until the system performs at the level the customer and you expect.

If you want to understand how enterprise AI actually gets deployed at scale, not in theory but in production, this is that role.

What You'll Own

Customer Discovery and Scoping

  • Deeply understand each customer's business and existing call workflows.
  • Map their full tech stack: telephony dialer, payment processors, portals, CRMs, and the APIs connecting them
  • Design call flow diagrams and interaction maps that translate customer workflows into precise agent behaviours
  • Translate complex, sometimes ambiguous requirements into clear, actionable scopes for engineering

Deployment and Phased Delivery

  • Own end-to-end delivery across multiple deployment phases
  • Manage 4 to 6 concurrent deployments with strong project governance, clear milestones, and zero surprises for the customer
  • Drive all customer-facing calls, from kickoff through go-live, with clarity, confidence, and follow-through

Agent Validation and Performance

  • Design comprehensive scenarios covering happy paths, edge cases and adversarial situations to ensure the agent is production-ready
  • Conduct test calls alongside Agent Engineers to evaluate agent performance across real-world conditions
  • Own the feedback loop: test → identify gaps → brief the Agent Engineer → retest → validate and approve

Post-Go-Live Ownership

  • Stay close after launch: track agent KPIs, surface performance issues, manage post-production bugs, and drive continuous improvement
  • Lead phased expansion, each new capability is a new deployment with its own scoping, testing, and go-live cycle
  • Serve as the primary escalation point until the deployment reaches a stable, handoff-ready state

Stakeholder Management

  • Navigate multi-stakeholder customer environments: CXOs, Operations, Compliance, IT, and Tech teams, each with different priorities and vocabularies
  • Be the person customers trust - responsive, on top of every commitment, and always a step ahead
  • Internally, work across functions to unblock delivery and represent the customer's reality

Who You Are

  • 2+ years of work experience in B2B SaaS, consulting, digital transformation, or technical deployments/ implementations
  • Experience deploying or managing voice AI agents, conversational AI, or automation systems is a strong plus
  • Familiarity with the US consumer finance or debt collections industry is a plus, not a requirement
  • You understand how APIs work, can read a basic integration spec, and can hold a credible technical conversation without being an engineer
  • You're the kind of person who anticipates problems before they surface and builds for them
  • Strong communicator, equally comfortable presenting to a CXO and working through an escalation path with an engineer
  • You thrive in ambiguity and figure things out without waiting to be told how. This role comes with high ownership and low hand-holding by design
  • You'll report to the Head of Customer Success and Deployments
  • You'll be joining a growing deployment team
  • Experience working with or for North American customers is preferred

What You'll Learn

  • How to take AI agents from demo to production in one of the most regulated, high-stakes industries in the US
  • How to design and validate AI systems that are safe, compliant, measurable, and commercially meaningful
  • How enterprise telephony, payment infrastructure, and compliance requirements shape what AI can and cannot do in the real world
  • How to operate at the intersection of product, AI, and mission-critical customer communication

From day 1, Prodigal has been defined by talented, humble, and hungry leaders and we want this mindset and culture to continue to blossom from top to bottom in the company. If you have an entrepreneurial spirit and want to work in a fast-paced, intellectually-stimulating environment where you will be pushed to grow, then please reach out because we are looking to build a transformational company that reinvents one of the biggest industries in the US.

To learn more about us - please visit the following:

Our Story - https://www.prodigaltech.com/our-story

What shapes our thinking - https://link.prodigaltech.com/our-thesis

Our website - https://www.prodigaltech.com/ 

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What applying to Prodigal usually looks like

Based on publicly available information, candidates applying through greenhouse for roles at Prodigal can generally expect a process consistent with common Greenhouse-based hiring workflows. This typically starts with an online application and resume review, followed by a recruiter screening call to discuss background and role fit. Depending on the position, such as technical roles like ai-engineer or machine-learning-engineer, or business roles like account-executive, candidates may encounter skills assessments, take-home exercises, or technical interviews. The process may include multiple stages involving hiring managers, team members, or panel interviews, often conducted virtually. Communication is usually managed through automated updates and email notifications from the Greenhouse platform. Response times vary depending on the role and hiring team workload. Candidates should typically prepare to discuss relevant experience, technical skills, and cultural fit, as these are commonly emphasized throughout the evaluation process.

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