Overview

Educational Qualification • B.Tech./B.E.

Responsibilities

• Set the vision, strategy, and delivery roadmap for AI/ML services across Digital India platforms and cross-ministerial systems
• Lead the end-to-end delivery of the programme's portfolio of AI use cases across the capability teams, ensuring timely, high-quality, and measurable outcomes
• Establish and run programme governance — planning, prioritisation, risk management, and delivery reporting — and present progress and outcomes to NeGD leadership
• Own the programme budget and cost governance, ensuring efficient use of compute, infrastructure, and manpower against the approved envelope
• Own the AI/ML technical strategy and target-state architecture across capability teams — Document Intelligence; Conversational & Multilingual AI; Predictive Analytics; Visual AI & Identity Verification; Agentic AI & Workflow Automation; and Fraud & Anomaly Detection
• Set standards for model selection and build-versus-buy decisions, including the use of open-source and sovereign models, fine-tuning, retrieval-augmented generation, and prompting
• Act as the design authority for the programme, approving reference architectures, integration standards, evaluation frameworks, and inference and deployment patterns
• Ensure reusable AI components — APIs, SDKs, model cards, and templates — are produced to a common standard and published for cross-ministry reuse
• Mentor the AI teams and the capability-pod leadership, scaling the organisation in line with validated demand
• Direct and coordinate the programme's functional and technical resources as a single, integrated delivery organisation
• Establish the operating model, engineering standards, and delivery culture for a fast-growing national AI capability
• Establish MLOps/LLMOps practices — model lifecycle management, evaluation, monitoring for drift and quality, and reliable, cost-effective inference at production scale
• Govern the engagement of empanelled agencies at the discovered L1 rate card across resource, project, and turnkey modes — including agency selection, performance management, acceptance, and service levels
• Manage relationships with technology, model, and infrastructure providers, including commercial terms, performance, and risk
• Ensure all AI systems are delivered in line with the Responsible AI framework — risk assessment, human oversight, explainability, evaluation, and audit
• Ensure security and data protection by design across the programme, in line with MeitY security standards, CERT-In directions, and the Digital Personal Data Protection Act, 2023
• Ensure the appropriate use of sovereign infrastructure and coordinate with other MeitY agencies where relevant
• AI/ML & Generative AI: Strong command of the modern AI stack — large language models, transformer architectures, generative AI, natural language processing, agentic AI, retrieval-augmented generation, computer vision, and classical and predictive machine learning
• MLOps & LLMOps: Model lifecycle management, training and inference pipelines, model registries, evaluation harnesses, monitoring for drift and quality, and reliable production deployment
• Solution & Platform Architecture: Microservices, event-driven and API-based design, model gateways, and multi-cloud, on-premise, and sovereign deployment patterns
• Generative AI Systems: Retrieval-augmented generation pipeline design, vector databases and semantic search, prompt and evaluation strategies, and output safety and guardrails
• AI Evaluation & Assurance: Evaluation frameworks, benchmarking, and red-teaming for accuracy, fairness, robustness, and safety
• Cloud & Inference Infrastructure: Cloud architecture, identity and access management, GPU/accelerator utilisation, scalability and reliability, and observability
• Cost Governance: Unit economics and cost management for compute, training, and inference, and forecasting against a programme budget
• Programme & Delivery Management: Programme governance, portfolio prioritisation, budgeting, risk management, and multi-workstream delivery
• Security, Data Protection & Responsible AI: Access control, encryption, audit, the Digital Personal Data Protection Act 2023, CERT-In directions, MeitY security standards, and the IndiaAI Responsible AI framework
• Organisational Leadership: Organisation design, hiring and capability development, performance management, and the management of delivery partners and vendors
• Communication & Stakeholder Engagement: Executive communication of strategy, progress, and risk; leading technical reviews; and building alignment across technical and functional teams

Qualifications

• 15+ years of experience in AI/ML, software, or data engineering, with a substantial record of senior technical and organisational leadership
• Proven experience leading the design, delivery, and operation of AI/ML, Generative AI, or large-scale data-intensive systems in production
• Extensive people-leadership experience, having led multi-disciplinary engineering and data-science organisations, including managers and technical leads
• Track record of delivering large, multi-workstream technology programmes to schedule and budget, with accountability for outcomes, quality, reliability, and cost
• Demonstrated experience owning technology strategy and architecture for an enterprise or platform operating at scale
• Strong, current technical grounding in AI/ML and modern software architecture, with the standing to set technical direction and make model and architecture decisions
• Prior Government/PSU experience is not essential; the ability to operate within public-sector requirements for data protection, sovereign infrastructure, procurement, and audit is expected

Education

• B.Tech./B.E. in Computer Science, Information Technology, Artificial Intelligence, or a related engineering discipline (Must have)
• M.Tech./M.S. in AI/ML, Computer Science, Data Science, or a related field strongly preferred; Ph.D. in a relevant field desirable
• Certifications (Desirable): Cloud/architecture professional (AWS/Azure/GCP), MLOps/LLMOps, or programme-management certifications (PMP, PRINCE2, SAFe)