Head Of Engineering

About the Role

Reliance Industries Limited (RIL) in partnership with a Big Tech MNC is launching a transformative new venture in Enterprise AI, and we are looking for a seasoned Head of Engineering to lead the charge. This role will be pivotal in building and scaling the engineering organization, setting the technical vision, and delivering AI-powered products that serve both enterprise and consumer needs.

As the Head of Engineering, you will define and execute the technical roadmap aligned with RIL's ambitious vision for Enterprise AI. You will lead cross-functional collaboration across product, research, data science, and business teams, while forging strategic partnerships with industry leaders and clients. You will also drive operational excellence, compliance, and foster a high-performance culture within the leadership team.

You will act as a key representative of RIL Intelligence at industry events and with stakeholders, playing a critical role in scaling the business and ensuring long-term profitability.

Key Responsibilities

• Define and execute the AI technology roadmap in alignment with product and business goals.
• Lead AI/ML R&D efforts, ensuring cutting-edge innovations in LLMs, NLP, computer vision, and predictive analytics.
• Oversee the architecture and development of AI-powered enterprise platforms, cloud, and GPU hosting infrastructure.
• Ensure robust scalability, security, and compliance with enterprise AI solutions.
• Drive technical hiring, mentorship, and foster a culture of innovation within the engineering team.
• Build teams from the ground up, with the expectation of scaling and leading both India-based and globally distributed engineering teams over time.
• Be hands-on with engineering teams—contributing to code and defining engineering frameworks, not just providing strategic direction.
• Collaborate with the Head of Product to align technical feasibility with market needs.
• Work with the Head of Finance and Procurement to communicate and plan infrastructure needs—GPUs, cloud, servers, data centers, and software.
• Implement AI ethics, responsible AI principles, and governance frameworks across product development.
• Stay up to date with emerging AI technologies, relevant patents, and evolving regulatory standards.

Core Deliverables

• AI Research: fine-tuning, RLHF, Evaluation
• ML Eng: Pipelines, labelling workflows, retraining, monitoring
• Product Eng: APIs, Frontend, business logic, use-cases
• Infrastructure: Clusters, model-serving infra, CI/CD, MLOps

Qualifications & Experience

• 10–15+ years in AI/ML engineering, software architecture, or deep-tech leadership roles.
• Strong grasp of AI model deployment, vector databases, and AI inference optimization.
• In-depth understanding of API-first design, data pipelines, and AI model integration in enterprise applications.
• Hands-on experience with cloud platforms (AWS, Azure, GCP), MLOps practices, and AI/ML model development.
• Proven expertise in building scalable, distributed systems, and enterprise-grade AI infrastructure.
• Experience in delivering B2B AI solutions that meet high standards of security and regulatory compliance.
• Demonstrated ability to lead AI research, manage engineering teams, and run innovation labs effectively.
• Startup DNA / Zero-to-One Operator – Proven track record of building and scaling systems from the ground up in highly ambiguous environments. Operates effectively without a playbook and brings strong judgment on when to prioritize speed versus precision.
• Cross-Functional Collaboration – Skilled at partnering with product, research, business, and design teams to align on priorities, shape strategy, and drive measurable outcomes.
• Navigating Complexity – Adept at balancing agility with accountability in fast-paced, regulated, and multi-stakeholder environments, ensuring progress without compromising governance or compliance.

Success Criteria:

• Build a founding engineering team with clear accountability
• Ship first production AI use case or MVP
• Build backend infra for the product/platform
• Deliver on 3+ core AI/ML use cases
• Highly visible role that requires candidate to win the trust of cross-functional and JV leadership