Director / Senior Engineering Manager, AI Innovation Factory (India)

Req ID: 341180 

NTT DATA strives to hire exceptional, innovative and passionate individuals who want to grow with us. If you want to be part of an inclusive, adaptable, and forward-thinking organization, apply now.

We are currently seeking a Director / Senior Engineering Manager, AI Innovation Factory (India) to join our team in Bangalore, Karnātaka (IN-KA), India (IN).

Role Overview This role leads the India hub of our AI Innovation & Demo Factory with day-to-day technical and administrative oversight. The leader partners closely with the Global AI Innovation Factory leader (USA) on escalations and portfolio management and serves as our "eyes on the ground" in India. They balance hands-on credibility with organizational scale, coaching managers and senior ICs across Generative & Agentic AI, enterprise data, cloud, and DevOps/MLOps, and collaborate across US/UK/EU/APAC/Middle East time zones. Department Reports to Location AI Innovation & Demo Factory Global AI Innovation Factory Leader (USA) India (Bengaluru/Hyderabad /Pune; hybrid/remote) Team Scope 30–40 FTEs (Mgrs, SAs, SW Eng, Data/ML Eng, MLOps/DevOps, Agent/Prompt Eng, QA) Purpose Provide on-the-ground technical leadership for the India AI Innovation Factory while partnering with the Global leader on escalations and portfolio direction. Ensure consistent, high-quality delivery of cross-industry Generative & Agentic AI solutions and convert emerging tech into repeatable client value. Key Responsibilities Primary (≈70%) • Technical Oversight & Governance — establish reference architectures for GenAI/agentic systems (tool/function calling, RAG, orchestration), SDLC/DevOps/MLOps, cloud/data/security, and component reuse; serve as the on-the-ground technical steward in India and partner with the Global AI Innovation Factory leader on technical escalations and standards. • Portfolio & Delivery Leadership — in partnership with the Global AI Innovation Factory leader, plan and track a multi-client portfolio; drive on-time, high-quality releases; unblock teams; maintain a backlog aligned to global roadmaps. • People Leadership (30–40) — hire, level, and coach managers/tech leads; define career paths; manage utilization/bench plans; run a learning cadence. • Executive & Stakeholder Engagement — present roadmaps/solution options to senior clients and internal executives; translate technical detail into business outcomes; influence decisions across regions. • Cross-Region Collaboration — coordinate standards and follow-the-sun delivery with US/UK/EU/APAC/Middle East; ensure robust handoffs and incident procedures. • Major Program Engagement — for flagship initiatives (e.g., Sugoi.AI), maintain a working knowledge of scope, status, and risks across 2–3 concurrent initiatives and participate in occasional client-facing interactions (e.g., steerco, workshops) in partnership with the Global leader. Secondary (≈30%) • Administrative & Operational Excellence — collaborate closely with the India Program Manager (who owns budget and forecast) on forecasting, vendor management, compliance, delivery KPIs, and staffing plans. • AI Innovation Factory Best Practices Integration — integrate AIF standards, reference architectures, and accelerators into local delivery; collaborate with the central Practice team that owns overall practice development. • Risk & Quality Management — proactively manage delivery, security, privacy, and regulatory risks; run design/architecture reviews and go/no-go checks. Required Qualifications • 12–18+ years in software/consulting with 5+ years leading 25+ engineers (multi-team or program scale). • Proven delivery of cross-industry solutions combining enterprise data, cloud, DevOps/MLOps, and Generative/Agentic AI (not research-only roles). • Prior hands-on engineering background (e.g., Python/Java/C#) with ability to dive deep as needed without day-to-day coding. Technical Competencies (Weighted) Skill Area Proficiency What “Good” Looks Like Generative & Agentic AI Advanced Enterprise Architecture Advanced Shipped agentic systems (tool use, planning, orchestration), RAG pipelines, evaluation/guardrails; platform fluency. Multi-team planning, estimation, roadmapping, cross-region coordination; PoC→productization. Integrates AI with identity, data platforms, APIs, events, observability, CI/CD; sets NFRs (SLA/SLO, cost, resiliency). Cloud & Data Foundations DevOps/MLOps Software Delivery at Scale Advanced Advanced Advanced Azure/AWS/GCP; data governance, lineage, security, PII controls; pragmatic build vs. buy. IaC, testing strategies for AI apps, model/agent evaluation & monitoring, incident/rollback playbooks. Leadership & Behavioral Competencies • People leadership at scale — org design for 30–40; coaching managers; performance and succession systems. • Executive communication — C-suite-ready narratives; clear trade-offs; cross-cultural facilitation. • Consulting mindset — value cases; scope control; stakeholder alignment. • Bias for pragmatism — incremental delivery; maintainable patterns over novelty. • Ownership & autonomy — independent operation within global guardrails; proactive risk escalation. Success Metrics First 30 Days • Org & portfolio health baseline; confirm standards and escalation paths with the Global leader. • Skills heatmap and staffing plan; agree operating cadence with US leadership. First 60 Days • Align to global reference architectures/checklists; close top 3 delivery risks. • India talent plan (hiring, leveling, upskilling) and utilization targets. First 90 Days • ≥90% on-time delivery for in-flight work; standardize code quality gates and release process. • Publish India playbook for ways of working, SRE/MLOps, security guardrails, reuse catalog. 6–12 Months (Run-State) • Delivery: ≥92% on-time, ≤3% escaped defects; healthy DORA-style metrics for AI apps. • Reuse: ≥30% builds leverage approved accelerators/reference components. • People: <10% regretted attrition; >80% engagement; internal mobility in key roles. • Financial: within budget ±5%; utilization within target band. • Stakeholders: Exec CSAT ≥4.5/5 on quarterly reviews

About NTT DATA

NTT DATA is a $30+ billion business and technology services leader, serving 75% of the Fortune Global 100. We are committed to accelerating client success and positively impacting society through responsible innovation. We are one of the world’s leading AI and digital infrastructure providers, with unmatched capabilities in enterprise-scale AI, cloud, security, connectivity, data centers and application services.  Our consulting and industry solutions help organizations and society move confidently and sustainably into the digital future. As a Global Top Employer, we have experts in more than 50 countries. We also offer clients access to a robust ecosystem of innovation centers as well as established and start-up partners. NTT DATA is part of NTT Group, which invests over $3 billion each year in R&D.