Chief Technology Officer

Chief Technology Officer (CTO) / SVP – Engineering (AI Platforms & Agentic Systems)

Location: Gurgaon or Bangalore (Onsite / Hybrid)

Budget : 6-8 Cr

Experience:

• 18–25 years of overall engineering experience with 5+ years in senior leadership roles (VP / SVP / Head of Engineering / CTO).
• Proven experience building and scaling large-scale, production AI platforms .
• Minimum 3+ years of hands-on leadership in GenAI and Agentic AI , where systems are live and delivering measurable business impact .
• Strong background in technology and engineering , not Data Science only or Product Management–led careers.
• Experience scaling engineering teams in high-growth startups or complex enterprise environments .

Role Overview:

We are seeking a visionary CTO / SVP Engineering to lead the design, execution, and scale-up of live, production-grade Agentic AI and Generative AI platforms that are already driving measurable business impact .

This role is strictly for deep engineering leaders who have grown through backend, platform, distributed systems, and cloud engineering , and who have hands-on leadership experience shipping GenAI / Agentic AI systems into production, not research prototypes.

You will own technology strategy, architecture, and execution , building AI-first platforms that transform enterprise workflows using autonomous agents, LLM-powered systems, and intelligent decision engines , while scaling and mentoring large, high-performing engineering organizations.

Key Responsibilities:

1. AI & Platform Strategy Leadership

• Define and execute the Agentic AI and Generative AI engineering roadmap aligned with business growth and product vision.
• Lead architecture and delivery of autonomous agents, multi-agent orchestration frameworks , and tool-augmented LLM systems in production.
• Drive adoption of advanced GenAI patterns including RAG, fine-tuning, prompt orchestration, agent planning, memory systems , and evaluation pipelines.
• Establish standards for AI safety, governance, observability, monitoring, and cost optimization at scale.
• Ensure AI systems deliver real business outcomes —revenue growth, efficiency gains, and customer impact.

2. Engineering & Architecture Excellence

• Own end-to-end architecture for scalable, secure, highly available AI platforms.
• Lead modernization toward cloud-native, event-driven, microservices-based, and distributed architectures .
• Ensure engineering excellence across performance, reliability, scalability, security, and resilience .
• Partner closely with Product, Data, and Research teams to convert AI innovation into production-grade systems .
• Drive strong DevOps / MLOps practices for faster, safer deployments.

3. Organizational & People Leadership

• Build, scale, and lead large multi-disciplinary engineering organizations (Backend, Platform, AI/ML Engineering, Infrastructure, DevOps).
• Mentor and grow senior leaders (VPs, Directors, Principal/Staff Engineers), creating a strong succession pipeline.
• Foster a culture of engineering rigor, ownership, accountability, and continuous learning .
• Drive execution through OKRs, delivery metrics, platform health indicators, and engineering KPIs .

4. Executive & Business Partnership

• Act as a strategic technology partner to the CEO, C-suite, and Board.
• Translate AI and platform capabilities into clear business value and growth narratives .
• Lead build vs. buy decisions , vendor selection, and AI ecosystem partnerships.
• Support go-to-market initiatives by enabling AI-led product differentiation and scale .
• Represent engineering in investor, customer, and partner discussions with credibility and depth.