Job Description
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 Gen AI 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 Gen AI / 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 Gen AI 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 Dev Ops / 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, Dev Ops).
- 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.
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 Gen AI 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 Gen AI / 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 Gen AI 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 Dev Ops / 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, Dev Ops).
- 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.
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