New opportunity

S&C GN - TS&T – Enterprise AI Value Strategy - Senior Manager

Accenture · Gurugram, India

About this role

Accenture’s Technology Strategy & Transformation practice seeks a Senior Manager to help global clients adopt AI-native software delivery at scale and realize measurable value from AI in software engineering. The role advises CIOs, CTOs, CDOs and engineering leaders on changes to how software is designed, built, tested, secured and delivered.

Responsibilities

Define enterprise AI-powered software delivery transformation strategies and translate them into executable approaches.
Define the target-state software development life cycle (SDLC), platform and tooling strategy and architecture, engineering productivity measures, delivery operating model changes and value-realization measures.
Set process-reinvention agendas across accounts, shape enterprise agentic architecture and operating-model change, build the practice, and own a book of business.

Requirements and location:

The job description specifies 14+ years of experience; the posting header separately lists 12–14 years.
Listed locations are Bangalore, Gurugram, Mumbai, Pune, Chennai, Kolkata and Hyderabad. The position is full-time.

For full details about this role, click “Apply on company site” to view the employer’s original posting.

Skills for this role

Enterprise AI strategyAI-native software engineeringAI-powered software deliveryAgentic architectureSoftware development life cycle (SDLC)Platform strategyTooling strategyEnterprise architectureEngineering productivity measurementOperating model designValue realizationExecutive stakeholder managementPortfolio management

Checking your profile…

Preparation suggestions, not the employer’s actual interview questions. Always check the original posting for current requirements.

Understand the role

What matters most

Turn AI strategy into an executable transformation
The role defines AI-powered software delivery strategies for global clients and translates them into approaches enterprises can implement at scale.
Design the target-state delivery system
The posting calls for a target-state SDLC, platform and tooling strategy and architecture, and changes to how software is designed, built, tested, secured and delivered.
Make productivity and value measurable
Defining engineering productivity measures and measurable value realization is central to the stated goal of turning AI adoption into enterprise outcomes.
Lead enterprise and account-level reinvention
This Senior Manager advises CIOs, CTOs, CDOs and engineering leaders, sets process-reinvention agendas across accounts, and shapes agentic architecture and operating-model change.
Build the practice and own a book of business
The posting explicitly describes the role as a portfolio owner and enterprise advisor who builds the practice and owns a book of business.

Likely challenges to think through

Scaling AI without weakening delivery controls
A likely challenge is balancing faster AI-assisted delivery with testing, security and consistent ways of working across an enterprise; this is a preparation hypothesis, not a reported client problem. Prepare an example of how you would phase SDLC, platform and operating-model changes while checking quality and security.
Separating AI impact from general improvement
Because the role must define productivity and value-realization measures, a likely difficulty is distinguishing AI-driven gains from other delivery changes. Prepare a measurement approach with a baseline, outcome measures and a way to account for changes in work mix or quality.
Balancing client-specific change with portfolio ownership
The remit spans executive advice, agendas across accounts, practice building and a book of business. A likely trade-off is tailoring transformation plans to each client while developing approaches that can be used across the practice. Prepare to explain how you would make that distinction without assuming a fixed Accenture methodology.

Practice your answers

Technical practice

Suggested practice question: How would you turn an enterprise AI software-delivery ambition into an executable transformation strategy?

What to coverThe role calls for defining transformation strategies and translating them into executable approaches. As preparation, explain how you would establish a baseline, sequence changes across the delivery lifecycle, and connect the plan to measurable outcomes.

Suggested practice question: What would you consider when defining a target-state SDLC for AI-native software delivery?

What to coverThe posting explicitly names the target-state SDLC and changes to how software is designed, built, tested, secured and delivered. As preparation, discuss where AI could change workflows, what oversight remains necessary, and how you would evaluate the target state against current delivery.

Suggested practice question: How would you develop an enterprise platform and tooling strategy for AI-powered delivery?

What to coverPlatform and tooling strategy and architecture are stated responsibilities. As preparation, describe how you would assess integration with existing engineering workflows and weigh consistency at scale against the needs of different teams.

Suggested practice question: How would you approach enterprise agentic architecture?

What to coverThe Senior Manager is expected to shape enterprise agentic architecture. As preparation, explain how you would define agent responsibilities and boundaries, account for human oversight, and evaluate whether the architecture supports the intended delivery outcomes.

Suggested practice question: How would you protect testing quality and security as AI changes software delivery?

What to coverThe posting identifies testing and securing software as parts of the work being rethought with AI, alongside a goal of quality uplift. As preparation, discuss how you would assess changes to verification and review practices without assuming that faster delivery means better quality.

Suggested practice question: How would you measure engineering productivity in an AI-powered delivery transformation?

What to coverDefining engineering productivity measures is an explicit responsibility. As preparation, explain how you would establish a baseline and interpret measures alongside quality and delivery outcomes, including the risk of mistaking activity for value.

Suggested practice question: How would you demonstrate value realization from AI in software engineering?

What to coverThe role aims to turn transformation ambition into measurable outcomes and calls for value-realization measures. As preparation, describe how you would link delivery changes to enterprise value, test whether observed improvements are credible, and adjust the approach when benefits do not materialize.

Suggested practice question: What delivery operating-model changes might be needed for AI-native software engineering at scale?

What to coverThe posting calls for delivery operating-model change across enterprises. As preparation, discuss decision rights, team responsibilities and adoption trade-offs, while making clear that the appropriate design depends on the client's starting point.

Suggested practice question: How would you prioritize process-reinvention opportunities across accounts?

What to coverThe role sets a process-reinvention agenda across accounts and owns a book of business. As preparation, explain how you would compare opportunities by potential value and feasibility, then decide where to focus limited leadership and delivery capacity.

Behavioural practice

Suggested practice question: Tell me about a time you aligned senior technology leaders around a transformation direction.

What to coverThe role advises CIOs, CTOs, CDOs and engineering leaders. As preparation, use a real situation, your actions to address differing priorities, and the resulting decision or outcome.

Suggested practice question: Describe a time you led a change to an engineering delivery operating model.

What to coverOperating-model change is a stated part of the role. As preparation, give a real situation, explain how you handled adoption challenges and describe the observed result without overstating it.

Suggested practice question: Tell me about a time you prioritized competing opportunities across a portfolio or multiple accounts.

What to coverThe posting describes a portfolio owner who sets an agenda across accounts and owns a book of business. As preparation, explain the situation, the criteria and actions behind your choice, and what resulted.

Suggested practice question: Describe a time you helped build a practice or capability while delivering client work.

What to coverBuilding the practice is an explicit responsibility. As preparation, give a real example of the need you identified, what you personally did, and the outcome for the practice or its clients.

Sharpen your knowledge

Topics to prepare

AI-native software delivery strategy
The role calls for enterprise AI-powered software delivery strategies. Revise how a strategy connects changes in engineering work to executable steps; as an exercise, outline the decisions a hypothetical CIO would need to make before scaling adoption.
Target-state software development life cycle
The posting explicitly covers how software is designed, built, tested, secured and delivered. As an exercise, compare a current-state and target-state SDLC, identifying where AI changes work and where controls remain necessary.
Agentic architecture, platforms and tooling
The role includes shaping enterprise agentic architecture and defining platform and tooling strategy and architecture. As an exercise, sketch a conceptual target architecture and explain its integration and governance decisions without assuming a particular product.
Process reinvention and delivery operating models
The Senior Manager sets process-reinvention agendas across accounts and shapes operating-model change. As an exercise, map how decision rights, engineering workflows and team responsibilities might change in a hypothetical transformation.
Engineering productivity and value realization
The posting calls for productivity measures, quality uplift and measurable enterprise value. As an exercise, distinguish delivery measures from business outcomes and note what baseline each proposed measure would need.

Skills to revise

Build an executable transformation approach
Practice turning a hypothetical client ambition into a phased plan with decisions, dependencies and measurable outcomes. This reflects the stated responsibility to translate AI-powered software delivery strategy into an executable approach.
Draft a measurement scorecard
Create a short example scorecard covering engineering productivity, quality and value realization; specify baselines and how results would be interpreted. The posting explicitly asks for these measures.
Present an executive recommendation
Rehearse a concise recommendation to a CIO, CTO or CDO that explains the target state, operating-model implications and value case. Advising these leaders is central to the advertised role.
Prioritize an account portfolio
As a preparation exercise, compare a few hypothetical account opportunities and explain which reinvention agenda to pursue first. This is a suggested way to practise the posted responsibilities to set agendas across accounts, build the practice and own a book of business.

Your preparation checklist

Prepare an AI-native delivery case walkthrough
Choose a real project you can discuss and outline the starting problem, your decisions, the changes to software delivery, and measured results. The role focuses on scaling AI-powered delivery and realizing value.
Draft a target-state SDLC design
As an interview exercise, sketch how AI could change design, build, test, security and delivery. Show the platform and tooling choices, architecture trade-offs, and a phased approach to implementation.
Build a productivity and value scorecard
Propose a small set of measures for engineering productivity, quality and enterprise value. Explain baselines, how each measure would be tracked, and how you would avoid attributing every change to AI.
Map an agentic architecture and operating-model change
Prepare a one-page proposal showing where agents might fit in enterprise delivery, which decisions remain with people, and what team or process changes would be needed. Treat it as a proposed approach, not an Accenture-prescribed design.
Gather evidence of senior-level account leadership
Prepare examples you can substantiate of advising senior technology leaders, setting a transformation agenda across accounts, developing a practice or managing a book of business. These activities are explicitly part of the role.
Rehearse an executive recommendation
Turn one of your examples into a brief CIO- or CTO-level presentation: the decision needed, expected value, implementation choices, risks and measures of progress.
Write focused questions for the employer
Ask how the team defines measurable value, where clients are in adopting AI-native delivery, and how this Senior Manager role balances enterprise advisory work with practice building and business ownership. You can also clarify the posting’s 12–14-year header versus its 14+-year description.

Availability last checked: 4 Nov 2026. Status can change after a check; confirm on the employer’s website. Report an issue · Our checking policy

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