Title:  Engineering Manager, D&T, Applied AI

Job Summary

We are looking for an Engineering Manager, D&T, Applied AI to lead the design, build, and scale-out of AI-powered digital products and platforms across the enterprise. This leader will combine strong technical depth with calm, execution-focused people leadership to help turn AI opportunities into secure, scalable, production-ready solutions.

This role is suited for a future-oriented engineering leader who is energized by ambiguity, willing to take thoughtful risks, and able to balance speed with sound engineering judgment. The ideal candidate can lead technical teams through fast-moving change, drive adoption of Applied AI and Generative AI in practical business use cases, and create an environment where experimentation, accountability, and composure go together.

While this role will partner across enterprise functions, it should also remain grounded in hands-on engineering leadership, modern platform thinking, and a strong understanding of how to operationalize AI responsibly in a regulated business environment.

Essential Duties and Responsibilities

• Lead multiple engineering teams delivering Applied AI products, intelligent workflows, and enterprise AI capabilities from idea through production.
• Translate business priorities into an actionable AI engineering roadmap with clear technical milestones, success metrics, and delivery plans.
• Drive end-to-end execution across AI use cases such as copilots, knowledge assistants, intelligent automation, predictive insights, document intelligence, and agentic workflows.
• Build and scale modern AI engineering capabilities spanning application engineering, data pipelines, model integration, API services, evaluation, observability, and platform reliability.
• Establish an engineering culture that values experimentation, rapid prototyping, measurable learning, and disciplined production hardening.
• Make thoughtful build-vs-buy decisions across foundation models, cloud AI services, orchestration frameworks, data platforms, and internal reusable components.
• Partner with product, architecture, data, security, infrastructure, and business leaders to identify high-value AI opportunities and accelerate adoption.
• Ensure AI solutions are secure, scalable, governable, and aligned with enterprise architecture and compliance expectations.
• Lead technical decision-making across cloud-native architectures, AI application patterns, system integrations, and platform design.
• Build, coach, and retain high-performing engineering talent, including engineering leads, software engineers, data engineers, and AI/ML engineers.
• Develop strong engineering managers and technical leads by setting clear expectations around delivery, architecture quality, operational excellence, and people growth.
• Create a high-trust team environment where individuals can move quickly, speak openly, manage risk intelligently, and stay composed under pressure.
• Drive engineering excellence through CI/CD, automated testing, telemetry, cost discipline, incident learning, and reliable release practices.
• Stay current with external market developments in Applied AI, LLMs, AI agents, MLOps, and enterprise AI governance, and convert that insight into pragmatic internal action.

#LI-Hybrid  #LI-SM 

What Success Looks Like

• AI use cases move from pilot to production with measurable business value, adoption, and operational reliability.
• Engineering teams deliver at a sustainable pace with stronger clarity, ownership, and technical quality.
• The organization builds reusable AI patterns rather than isolated proofs of concept.
• Leaders trust the team to move fast without losing control of security, compliance, or platform stability.
• Teams are more confident operating in ambiguity and better able to balance innovation with delivery discipline.

Required Qualifications

• Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field.
• 10+ years of experience in software engineering, platform engineering, data engineering, or AI/ML engineering.
• 3+ years of people leadership experience managing engineering teams in a product, platform, or enterprise technology environment.
• Experience delivering production-grade cloud-native solutions on Azure or a comparable hyperscale cloud platform.
• Experience leading engineering teams that build enterprise applications, APIs, data services, and scalable distributed systems.
• Demonstrated experience applying AI/ML or Generative AI to real business problems beyond experimentation alone.
• Strong experience with agile delivery, engineering planning, stakeholder management, and cross-functional execution.
• Strong communication skills with the ability to align technical teams and senior business stakeholders around priorities and trade-offs.

Preferred Knowledge, Skills and Abilities

• Experience building Applied AI solutions using LLMs, retrieval-augmented generation, vector search, agentic workflows, model evaluation, and prompt or workflow orchestration.
• Experience with enterprise data and analytics platforms such as Microsoft Fabric, Azure Data Factory, Databricks, Synapse, or similar technologies.
• Familiarity with MLOps and LLMOps practices including deployment pipelines, experiment tracking, model monitoring, offline and online evaluation, and observability.
• Experience with AI governance, model risk controls, privacy, bias awareness, and human-in-the-loop operating models.
• Experience in regulated industries such as healthcare, pharmaceuticals, medical devices, or manufacturing.
• Exposure to connected systems, IoT, digital manufacturing, or edge-enabled use cases is a plus.
• Experience hiring and growing teams in the Bangalore market, including building strong local technical leadership.

Leadership Profile

We are looking for a leader who is:

• Dynamic in execution and able to convert emerging ideas into focused action.
• Future-looking and energized by the practical possibilities of AI, not just the hype.
• Comfortable taking smart, informed risks while keeping teams grounded and accountable.
• Composed under pressure and effective in fast-changing, high-ambiguity environments.
• Technically credible enough to challenge architecture, guide design choices, and coach engineers deeply.
• Strong at leading managers, senior engineers, and cross-functional teams without creating unnecessary process overhead.
• Curious, humble, and persistent, with a strong bias toward learning and continuous improvement.

Why This Role Matters

This role will help shape how D&T uses Applied AI to improve speed, quality, decision-making, and user experience across the enterprise. It is not a pure research role and not a traditional delivery manager role. It is a hands-on engineering leadership role focused on turning AI potential into durable business capability through strong teams, sound architecture, and bold but responsible execution.

Travel Requirements

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