Senior Vice President of Engineering Agentic AI
Questhiring
5 - 10 years
Gurugram
Posted: 12/02/2026
Job Description
Job Title: Senior Vice President (SVP) Engineering (Agentic AI & Generative AI)
Location: Bangalore/Gurgaon ( Onsite)
Experience: 1925+ years
Reporting to: Global CIO
Role Overview
We are seeking a visionary SVP of Engineering to lead large-scale engineering organizations building Agentic AI systems and Generative AI platforms. This role demands a rare blend of deep technical expertise, AI-first product thinking, and enterprise-scale engineering leadership.
You will own the architecture, execution, and evolution of AI-driven platforms, transforming business workflows through autonomous agents, LLM-powered systems, and intelligent decision engines, while scaling high-performing global engineering teams.
Key Responsibilities
AI & Platform Leadership
- Define and execute the Agentic AI and Generative AI engineering strategy aligned with business and product vision.
- Lead the design of autonomous AI agents, multi-agent orchestration frameworks, and tool-augmented LLM systems.
- Drive adoption of LLM architectures, including RAG, fine-tuning, prompt orchestration, memory systems, and agent planning.
- Establish best practices for AI safety, governance, observability, evaluation, and cost optimization.
Engineering & Architecture Excellence
- Own end-to-end system architecture for scalable, secure, and high-availability AI platforms.
- Lead modernization toward cloud-native, event-driven, and distributed systems.
- Ensure engineering excellence across performance, reliability, scalability, and security.
- Partner closely with Product, Data, and Research teams to translate AI innovation into production-grade systems.
Organizational Leadership
- Build and scale large multi-disciplinary engineering teams (Backend, Platform, AI/ML, Infra, DevOps).
- Mentor senior leaders (VPs, Directors, Staff Engineers) and build a strong engineering leadership bench.
- Foster a culture of innovation, ownership, accountability, and continuous learning.
- Drive execution through OKRs, delivery metrics, and engineering health indicators.
Executive & Business Partnership
- Act as a strategic partner to C-suite and Board, translating AI capabilities into business outcomes.
- Lead build vs buy decisions, vendor partnerships, and AI ecosystem collaborations.
- Support go-to-market strategies by enabling AI-led differentiation and scale.
- Represent engineering in investor, partner, and customer discussions.
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