Description
What You Will Do Delivery & Programme Leadership

-

Own end-to-end delivery of a $10M+ engineering portfolio across clients β€” on time, on budget, and to quality bar.

-

Lead platform build, modernisation, and custom application programmes natively on cloud, spanning .NET Full-Stack, Java Distributed Systems, Python stack etc.

-

Set and enforce engineering standards: architecture guardrails, code quality, DevSecOps, and release cadence across multi-team engagements.

-

Manage programme risk proactively β€” escalate early, resolve decisively, and keep clients informed throughout.

AI-Driven Engineering Acceleration

-

Embed AI tooling across the SDLC β€” from AI-assisted requirements and design through to automated testing, code generation, and incident response.

-

Architect and operationalise agentic systems and workflows that reduce manual toil, accelerate delivery cycles, and improve output quality.

-

Quantify the impact of AI adoption: establish baselines, track velocity and quality metrics, and present measurable efficiency gains to clients and leadership.

-

Stay ahead of the AI tooling curve; evaluate and pilot emerging platforms (LLM orchestration, RAG pipelines, AI code assistants).

Portfolio & Revenue Growth

-

Carry full P&L; accountability for the portfolio β€” margin, revenue, forecasting, and commercial hygiene.

-

Partner with practice, consulting, and client partner leaders to identify expansion opportunities within existing accounts and shape recent pursuit strategies.

-

Translate delivery track record into growth narrative β€” contribute to proposals, solution designs, and client presentations that differentiate on execution credibility.

Client & Stakeholder Engagement

-

Serve as the senior delivery point-of-contact for clients β€” build trust-based relationships at CTO/CIO/VP level.

-

Facilitate governance forums (steering committees, QBRs,



escalation calls) with clarity and confidence.

-

Align internal stakeholders β€” practice heads, resource managers, people leaders β€” to programme needs without bureaucratic drag.

People & Capability Development

-

Lead, mentor, and grow a high-performing engineering organisation; foster a culture of ownership and continuous improvement.

-

Champion individual upskilling β€” create structured learning pathways around AI, cloud, and modern engineering practices.

-

Spot and develop next-generation delivery leaders from within the team.

Responsibilities

What You Bring

Experience & Background

- 15–17 years in software engineering with a significant portion in leadership roles managing multi-team, multi-million-dollar programmes.

- Hands-on track record of delivering platform build, legacy modernisation, and greenfield application programmes on cloud β€” not just oversight, but technical depth you can draw on in client conversations.

Technical Stack & Architecture

- .NET Full-Stack (C#, ASP.NET Core, Azure-native services) and/or Java Distributed Systems (Spring Boot, microservices, Kafka, Kubernetes) β€” you can assess architecture quality, not just read status reports.

- Python stack experience (FastAPI, Django/Flask, pandas, NumPy) particularly for data pipelines, AI/ML integrations, and automation scripts.

- Cloud-native delivery on Azure, AWS, or GCP; Infrastructure as Code, CI/CD pipelines, container orchestration, and observability are second nature.





- Practical experience designing and deploying agentic AI systems β€” LLM orchestration, tool-use patterns, retrieval-augmented generation, and multi-agent workflows in an enterprise context.

AI & Automation Fluency

- Hands-on experience with enterprise AI coding and productivity tools β€” GitHub Copilot / Claude (Anthropic), and / or Cursor β€” applied meaningfully across design, development, review, and documentation phases of the SDLC.

- Understands where AI drives automation, acceleration, and efficiency within IT application landscapes β€” and equally where it introduces risk that must be managed, especially in regulated domains.

- Ability to differentiate between AI hype and production-ready tooling; pragmatic evaluator of what to adopt, when, and how.

Leadership & Commercial Acumen

- Proven P&L; ownership at $10M+ scale β€” comfortable with revenue forecasting, margin management, SOW negotiations, and change order governance.

- Excellent stakeholder management with both internal leaders and senior client executives; able to hold a room, manage difficult conversations, and build long-term advisory relationships.

- Growth mindset β€” actively invests in own learning and models the same for the team.

What Success Looks Like

OutcomeHow We Measure It
Delivery-led growthYear-on-year portfolio revenue growth; new SOWs sourced from existing accounts
Execution excellenceOn-time, on-budget delivery rate; CSAT scores; reduction in critical defect leakage
AI-driven efficiencyMeasurable reduction in manual effort and cycle times through AI tooling; documented ROI presented to clients
People & capabilityTeam retention, upskilling completion rates, and promotion pipeline health

Qualifications

B.E./B.Tech/M.E./M.Tech β€” Computer Science, Electronics & Telecom

Domain focus : Banking, Financial Services, Insurance, Retail & Consumer services

📌 Engineering & AI Delivery Leader (Pune)
🏢 Leading
📍 Pune