Sr Director, AI & Engineering (Hyderabad)

Overview

Senior Director role setting the enterprise engineering and AI-enabled development-lifecycle strategy for a portfolio of products and platforms, leading Directors, engineering managers and principal engineers.

What you'll do

• Set the enterprise engineering and AI-enabled development-lifecycle strategy, translating business priorities into a multi-year capability roadmap, investment thesis, target architecture and outcome framework.
• Lead Directors, engineering managers, principal engineers and cross-functional leaders; define organizational design, decision rights, workforce strategy, succession depth and leadership expectations across a broad span of control.
• Own the transformation from AI-assisted development to an AI-native operating model spanning discovery, specification, architecture, coding, review, testing, release, operations, knowledge management and continuous improvement.
• Establish enterprise guardrails for AI use in engineering, including approved tools and models, data and intellectual-property protection, human accountability, traceability, evaluation, access controls, model and prompt supply-chain risk, agent permissions, auditability, monitoring, rollback and retirement.
• Sponsor common developer platforms, reusable AI and agent capabilities, context and knowledge services, reference architectures, paved-road workflows and automated policy controls that enable teams to scale safely.
• Create portfolio governance for use-case selection and progression from experiment to production, applying value, risk, feasibility, architecture, data readiness, regulatory impact and total-cost criteria to build, buy, partner, scale or retire decisions.
• Define quality and safety standards for AI-generated and AI-enabled software, including specification quality, automated verification, secure development, adversarial and misuse testing, reliability engineering, observability, production evaluation and incident learning.
• Ensure increased engineering throughput does not compromise stability or maintainability by strengthening internal platforms, loosely coupled architectures, automated testing, version-control discipline, fast feedback loops and value-stream management.
• Own a balanced portfolio scorecard covering customer and business value, flow, adoption, quality, security, reliability, cost, developer experience, technical debt and AI risk; report outcomes and investment trade-offs to executive stakeholders.
• Build enterprise capability in product engineering, platform engineering, cloud, data, quality, security, reliability, AI engineering, agent orchestration, specification and context engineering, and critical evaluation of AI outputs.
• Partner with senior Product, Business, Security, Data, Legal, Privacy, Compliance and Operations leaders to align AI-enabled delivery with customer needs, regulatory obligations, enterprise risk appetite and commercial priorities.
• Represent engineering in enterprise planning, investment governance, vendor and strategic-partner decisions, executive risk reviews and major customer or regulatory engagements.

What you'll need

• Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, or equivalent practical experience.
• Typically 15+ years of progressive software engineering and technology leadership experience.
• 7+ years leading leaders and accountability for multiple teams, a major portfolio, or an enterprise engineering capability.
• Demonstrated success setting enterprise engineering strategy and delivering multi-year transformation across products, platforms, architecture, talent, operating model and production operations.
• Proven experience scaling AI-enabled development beyond individual tools or pilots, with measurable outcomes across the lifecycle and operating controls for security, privacy, intellectual property, quality, human oversight and responsible AI.
• Executive-level understanding of AI-assisted and agentic engineering, including model and tool evaluation, context and knowledge architecture, AI evaluation methods, LLMOps/MLOps, agent permissions and observability, and AI-specific software supply-chain risks.
• Strong record of leading Directors, managers, principal-level talent, global teams, vendors and strategic partners while building succession depth and durable organizational capability.
• Deep technology breadth across modern architecture, platform engineering, cloud, APIs, distributed systems, data, DevSecOps, quality engineering, observability, reliability, cybersecurity and regulated production operations.
• Track record of managing significant budgets, investment portfolios, vendor ecosystems and build-buy-partner decisions using value, risk, cost and strategic-fit criteria.
• Experience establishing measurable engineering and AI governance using portfolio metrics for value, throughput, stability, quality, security, cost, adoption, talent and customer outcomes.
• Experience in healthcare, life sciences, clinical, commercial, corporate or another regulated environment, including privacy, security, audit, validation and compliance expectations.
• Exceptional executive communication, organizational influence, change leadership, financial acumen and judgment in balancing innovation, delivery speed, risk, resilience and long-term maintainability.

Nice to have

• Advanced degree in technology, business or a related discipline.

Details

• Location: Hyderabad, India.
• Work mode: Hybrid.
• Travel required (up to 25%).
• This posting is intended for a possible upcoming opportunity rather than a live role.