AI Engineering Leader

About Us

We’re a team of hardworking, fun-loving, people-oriented technology enthusiasts passionate about helping clients thrive in a complex digital world. At Zensar, happiness is at the core of everything we do—from our Global Happiness Council to our annual Happiness Survey. Our employee value proposition—grow, own, achieve, learn (GOAL)—reflects the opportunities we foster for every employee. We work on diverse technologies across industries like banking, financial services, high-tech, manufacturing, healthcare, insurance, retail, and consumer services. Employees enjoy flexible work arrangements and a competitive benefits package, including medical, dental, vision, and 401(k).

Zensar is part of the $4.8 billion RPG Group, with 10,000+ innovators across 30+ global locations. Our culture is built on four core values: One Zensar, Nurturing, Empowering, and Client Focus.

About the Role

This full-time position offers excellent benefits and professional growth opportunities. As an AI Engineering Leader, you’ll drive delivery, innovation, and growth across a $10M+ engineering portfolio.

Responsibilities

• Delivery & Programme Leadership
  • Own end-to-end delivery of a $10M+ engineering portfolio—on time, on budget, and to quality standards.
  • Lead platform builds, modernizations, and custom applications natively on cloud (e.g., .NET Full-Stack, Java Distributed Systems, Python).
  • Set and enforce engineering standards: architecture guardrails, code quality, DevSecOps, and release cadence across multi-team engagements.
  • Proactively manage programme risk—escalate early, resolve decisively, and keep clients informed.
• AI-Driven Engineering Acceleration
  • Embed AI tooling across the SDLC—from AI-assisted requirements and design to automated testing, code generation, and incident response.
  • Architect and operationalize agentic systems to reduce manual toil, accelerate delivery, and improve output quality.
  • Quantify AI adoption impact: establish baselines, track velocity/quality metrics, and present measurable efficiency gains.
  • Evaluate and pilot emerging AI platforms (LLM orchestration, RAG pipelines, AI code assistants).
• Portfolio & Revenue Growth
  • Carry full P&L accountability—margin, revenue, forecasting, and commercial hygiene.
  • Partner with practice and client leaders to identify expansion opportunities and shape new pursuit strategies.
  • Translate delivery track record into growth narratives for proposals, solution designs, and client presentations.
• Client & Stakeholder Engagement
  • Serve as the senior delivery point-of-contact for clients—build trust with CTO/CIO/VP-level stakeholders.
  • Facilitate governance forums (steering committees, QBRs, escalation calls) with clarity and confidence.
  • Align internal stakeholders (practice heads, resource managers) to programme needs without bureaucratic drag.
• People & Capability Development
  • Lead, mentor, and grow a high-performing engineering organization; foster a culture of ownership and continuous improvement.
  • Champion individual upskilling—create structured learning pathways around AI, cloud, and modern engineering practices.
  • Spot and develop next-generation delivery leaders from within the team.

What Success Looks Like

• Delivery-led growth: Year-on-year portfolio revenue growth; new SOWs sourced from existing accounts.
• Execution excellence: On-time, on-budget delivery rate; CSAT scores; reduction in critical defect leakage.
• AI-driven efficiency: Measurable reduction in manual effort and cycle times through AI tooling; documented ROI.
• People & capability: Team retention, upskilling completion rates, and promotion pipeline health.

Requirements

• Experience & Background
  • 15–17 years in software engineering, with significant leadership experience managing multi-team, multi-million-dollar programmes.
  • Hands-on track record delivering platform builds, legacy modernizations, and greenfield applications on cloud—technical depth to assess architecture quality.
• Technical Stack & Architecture
  • .NET Full-Stack (C#, ASP.NET Core, Azure-native services) and/or Java Distributed Systems (Spring Boot, microservices, Kafka, Kubernetes).
  • Python stack (FastAPI, Django/Flask, pandas, NumPy) 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.
  • Practical experience designing/deploying agentic AI systems (LLM orchestration, tool-use patterns, RAG, multi-agent workflows).
• AI & Automation Fluency
  • Hands-on experience with enterprise AI tools (GitHub Copilot, Claude, Cursor) applied across the SDLC.
  • Understands AI’s role in automation, acceleration, and efficiency—and its risks in regulated domains.
  • Ability to differentiate AI hype from production-ready tooling; pragmatic adoption strategies.
• Leadership & Commercial Acumen
  • Proven P&L ownership at $10M+ scale—revenue forecasting, margin management, SOW negotiations, and change order governance.
  • Excellent stakeholder management with internal leaders and senior client executives.
  • Growth mindset—actively invests in learning and models the same for the team.

Qualifications

• B.E./B.Tech or M.E./M.Tech in Computer Science, Electronics & Telecom, or related field.
• Domain experience in Banking, Financial Services, Insurance, Retail, or Consumer Services.

Benefits

• Competitive benefits package: medical, dental, vision, and 401(k).
• Flexible work arrangements.
• Structured learning pathways and upskilling opportunities.
• Global Happiness Council and annual employee surveys.