Vice President Delivery

Gramener; Hyderabad; On-site; INR 5,000,000 - 9,000,000; Full time

Job summary

Gramener is seeking a Delivery Leader to own AI programs from scoping through production and live running. You will coordinate with engineering, architecture, data science and product teams while engaging client sponsors and senior stakeholders.

You will drive program governance, risk management and value delivery, ensuring quality and transparent reporting across multiple parallel streams. Strong executive communication and prior AI delivery in regulated environments are highly valued.

Qualifications

• 16 to 20 years in technology delivery with substantial AI/automation focus.
• Track record of taking AI programs from idea to production with measurable outcomes.
• Experience leading cross-functional teams across engineering, data science, architecture and business stakeholders.
• MBA or equivalent postgraduate qualification, or certifications such as PMP, MSP or AWS credential.

Responsibilities

• Own delivery for AI programs end to end from scoping to production.
• Set up program structure, governance, milestone plan and review schedule.
• Manage risk, early problem raising, and scope control to ensure business value.
• Lead client sponsorship interactions, steering committees and executive reviews.

Skills

AI delivery

Leadership

Program management

Stakeholder management

Education

MBA or equivalent postgraduate qualification

PMP/MSP/AWS credential

Tools

AWS

Job description

We are looking for a delivery leader who has taken AI programs all the way into production, at organisations where the outcome mattered and was measured. You will own how AI solutions are planned, built and delivered across our client programs, working with engineering, architecture, data science and product teams on one side, and with client sponsors and senior business stakeholders on the other.

WHAT YOU WILL DO

Programs and deliver yOwn delivery for AI programs end to end, from scoping and planning through to production and the first months of live running. Set up the program structure, governance, milestone plan and review schedule across several parallel workstreams. Manage risk actively. Raise problems early and make the decisions the team needs to keep moving. Keep scope honest, so that what gets built is what was agreed, and what was agreed still solves the business problem. Hold the quality bar on everything the team puts out, whether that is a model going live or a steering committee update. Own status reporting, risk and issue logs, change control and financial tracking, and report honestly against the value the program was meant to deliver .

Clients and stakeholders

Act as the senior point of contact for client sponsors and executives on the programs you lead. Run steering committees and executive reviews with the right level of detail for the audience, and put the real decisions on the table. Keep stakeholders informed often enough that a status update never comes as a surprise. Build relationships with client and internal leadership that last beyond the current program.

Technical judgement

Understand the full AI delivery lifecycle: data preparation, model development and evaluation, integration with enterprise systems, deployment, and monitoring once the solution is live. Work with architects, data scientists and engineering leads to sanity check the delivery approach and catch technical risk early. Hold your own in conversations about GenAI platform choices, LLM based applications, model governance and responsible AI, without needing to be the hands‑on expert. Know enough about cloud delivery, AWS in particular, to ask the right questions about how AI workloads will run and what they will cost. Make sure programs meet our compliance and responsible AI standards for transparency, auditability and human review.

Team Lead

delivery teams of project managers, business analysts, solution architects, data engineers and data scientists. Set clear standards for delivery, documentation, testing and communication, and hold the team to them. Stay close to the work without taking over from the people doing it. Spot skill gaps in the team and close them through hiring, training or partners. Build playbooks and templates that make the next program easier to run than the last one.

WHAT WE ARE LOOKING FOR

16 to 20 years in technology delivery, with a substantial part of it leading AI, data or automation programs for large organisations. A track record of taking AI programs from idea to production, owning the outcome rather than running someone else's plan. Experience leading teams that cut across engineering, data science, architecture and business stakeholders on complex programs. A background in consulting, systems integration or enterprise technology, where managing the client relationship was part of the job. Experience managing program budgets, staffing and delivery risk across several initiatives at once. Working knowledge of how AI solutions are built and kept running: data engineering, model development, integration, production support, and GenAI patterns such as LLM based applications. Working knowledge of cloud platforms, AWS preferred, and how AI workloads are usually set up and operated. Strong executive communication. Comfortable running steering committees, presenting to senior leadership, and explaining technical work to business audiences and the reverse. Experience handling difficult conversations on scope, quality, timelines and expectations, with clients and internally. Good to have AI delivery experience in regulated industries such as financial services, healthcare, media or public sector. Experience in or alongside an AI Center of Excellence or an enterprise AI platform team. An MBA or equivalent postgraduate qualification, or certifications such as PMP, MSP or an AWS crede nti al.