Lead Technical Program Manager
Mastercard is hiring a Lead Technical Program Manager in Pune, India. Level rates it ; you can apply on Mastercard.
Level's read on this job
- On Level's scale, this role is Works on AI ●●●○: the daily work is on AI products, without building the model.
- The posting mentions Copilot, M365 Copilot and technical program management among its tools and skills.
- Level classes it as a lead role.
- Mastercard has 1,100+ other open roles on Level.
- Posted within the past two weeks.
AI in this role
Lead technical program management across agent-amplified pods, using AI tooling and metrics to accelerate secure product delivery.
Our Purpose
Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential.
Title and Summary
Lead Technical Program ManagerAn AI‑First Technical Program Manager who organizes and accelerates delivery across agent‑amplified pods, using the written specification as the single source of truth and DORA/Core4 metrics as the primary delivery signal. Operates as a connective role in a shared pool — reaching into every pod to keep the program's coordination, risk, and dependency view current without orchestrating day‑to‑day — while preserving every SOX/PCI control gate. Manifest definitions, release integration, scope, and dependencies are tracked with data so all outputs are production‑ready at launch.Responsibilities
Organizes and accelerates related technology projects across multiple pods, aligning dependent organizations; identifies and removes blockers and always finds the path forward.
Charts the pod‑to‑pod relay (which pod builds each Epic stage), aggregates cross‑Big‑Rock risks and dependencies into a single view, and drives execution through the monthly Epic cycle anchored to the user guides.
Serves as the source of truth for status; generates the Monthly Technical Review (MTR), RAID Log, and DORA rollup directly from the session record using M365 Copilot, so the ledger stays current without hand‑keeping.
Measurably improves, streamlines, and eliminates excess process and ceremony — naming the reader of every artifact before it is kept and retiring legacy ceremonies deliberately.
Keeps abreast of the evolving AI‑engineering landscape; understands the practical read of what AI can and cannot do — that AI amplifies engineering judgment and leaves that judgment with the human — and asks the right questions to evaluate scalability, latency, security, performance, and data integrity.
Works with ambiguity and limited guidance, comfortable with the indeterminism of agent‑driven delivery, kept honest by the monthly user guides and real‑customer feedback.
Transforms raw thoughts into clear, concise communication and can communicate with confidence 3+ levels up; fluent in prompt patterns and agent‑session discipline to produce review‑ready output on the first pass.
Understands the needs of engineers and BizOps/SRE teams, including the verification tax and the build‑and‑review, follow‑the‑sun pairing that manages it.
Reviews metrics and proactively seeks improved data and mechanisms for visibility, keeping the program aligned to objectives while preserving all control gates — AIFE removes coordination overhead, not controls.
Plays an active role in mentoring, recruiting, and growing agent fluency and the Expert‑Generalist skill ladder across pods.
Experiences
Anticipate bottlenecks and factor in contingency for unplanned delays, including transition risk from Scrum to the pod model.
Define success metrics where they are missing, defaulting to the four DORA/Core4 metrics: Deployment Frequency, Lead Time for Changes, Change Failure Rate, and Failed Deployment Recovery Time.
Recognize discordant views and resolve them through constructive dialog; act as the program's anti‑confirmation‑bias check.
Continuously assess development processes, test plans, and operations to improve concurrent delivery, including tests‑first/spec‑driven parallelism and same‑session documentation currency.
Streamline or eliminate excess process wherever the same efforts or issues repeat year‑over‑year.
Expert with scrum delivery and its evolution into the AIFE monthly Epic and pod‑relay operating model, including the shift from story points to spec‑projected slices.
AI‑First Tooling & Skills
M365 Copilot fluency: Excel (RAID Log, dependency matrix, DORA dashboards), Word (MTR generation, handoff notes), Loop/OneNote (async session logs).
Spec‑as‑ledger discipline: treat the specification as reviewed engineering work; let agents project epic/feature/story records on demand rather than hand‑slicing or pointing.
Relay and shared‑pool operating model: chart pod relays, manage follow‑the‑sun handoffs, and steer by feedback at Epic boundaries.
Agent accountability and audit‑safety: ensure a named human directs and reviews every agent output, with session logs and control‑role sign‑offs keeping who‑built/who‑approved auditable.
Corporate Security Responsibility
All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must:
Abide by Mastercard’s security policies and practices;
Ensure the confidentiality and integrity of the information being accessed;
Report any suspected information security violation or breach, and
Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines.
How we rate this
Lead Technical Program Manager at Mastercard rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- Tell me about a project where technical program management was part of your work. What did you do?
- Tell me about a project where ai engineering was part of your work. What did you do?
- Tell me about a project where dora metrics was part of your work. What did you do?
- Tell me about a project where agile was part of your work. What did you do?
- Walk me through how you've used Copilot in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: Technical Program Management, AI Engineering, Dora Metrics, Agile, and Copilot. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
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