Director - Research & Development - Product Engineering Function

Role : Director - Research & Development

Department : Information Technology - AI & Product Development

Experience : 15-18 Years

Location: Chennai, Tamil Nadu - On-site

Employment Type: Full-Time, Permanent

Reporting To: SVP

Notice Period: Immediate Joiners Preferred / Short Notice Candidates Considered

About the Company

eNoah iSolution is a technology-driven global organisation focused on developing innovative AI-enabled products and enterprise solutions. The organisation is looking for an accomplished and forward-thinking R&D leader to drive its AI, machine learning, product engineering, and technology innovation initiatives from Chennai.

Role Overview

- We are looking for a Director - Research & Development to lead the organisation's R&D and Product Engineering function.

- This is a senior leadership opportunity for an individual with strong technical depth in Artificial Intelligence and Machine Learning, along with the strategic and organisational capability to drive product innovation, engineering excellence, operational scalability, and commercial outcomes.

- The ideal candidate should currently be operating at a Senior Manager or Associate Director level and be ready to take on broader Director-level accountability.

- The incumbent will lead a multidisciplinary team comprising ML Engineers, Data Scientists, Software Developers, Product Engineers, QA professionals, and Platform Engineering teams. The role will own the complete R&D lifecycle-from applied research and prototyping to production-grade deployment and platform operations.

- The position will work closely with the SVP, VP of Engineering, Product Management, and executive leadership to ensure that the R&D strategy aligns with business priorities, customer requirements, and the organisation's AI-first vision.

KEY RESPONSIBILITIES

Strategic Leadership & R&D Direction

- Define and execute the R&D strategy for AI, machine learning, and product development in alignment with organisational and business-unit priorities.

- Lead the overall R&D and Product Engineering function, providing strategic, technical, and operational direction.

- Drive the adoption of AI-enabled tools, automation, and modern engineering practices to improve delivery velocity, product quality, and operational efficiency.

- Track emerging technologies, market trends, competitor capabilities, and industry developments relevant to the organisation's products and platforms.

- Ensure proprietary technologies, processes, intellectual property, and technical innovations are documented, protected, and commercially leveraged.

- Act as the senior escalation point for critical technical, product, delivery, and operational matters.

Research & Innovation

- Identify, evaluate, and incubate emerging technologies across Machine Learning, Deep Learning, Generative AI, Large Language Models, Computer Vision, and Natural Language Processing.

- Lead applied research programmes, proof-of-concepts, experimentation, and prototypes that demonstrate measurable business value.

- Stay updated on academic research, open-source developments, AI frameworks, and competitor innovations.

- Define and execute the AI/ML product roadmap in line with strategic and commercial priorities.

- Establish experimentation frameworks, research standards, and reproducibility practices.

Product Development & Roadmap Governance

- Drive the complete product development lifecycle, including ideation, requirements gathering, architecture, prototyping, MVP

development, testing, productisation, and deployment.

- Translate research outcomes into robust, scalable, secure, and maintainable product capabilities.

- Ensure product roadmaps align with customer requirements, commercial objectives, regulatory obligations, and engineering feasibility.

- Lead product prioritisation by balancing customer value, operational impact, technical complexity, and delivery timelines.

- Support the evaluation of new products, integrations, platforms, and technology investments.

Engineering Delivery & Platform Operations

- Oversee software engineering activities across products and platforms, ensuring delivery against roadmap commitments and quality standards.

- Promote Agile and iterative delivery methodologies across engineering teams.

- Maintain visibility across engineering workloads, delivery schedules, technical debt, dependencies, risks, and resource

requirements.

- Oversee platform engineering, live services, CI/CD pipelines, development infrastructure, and operational tooling.

- Ensure platform security, service reliability, operational stability, scalability, and deployment automation.

- Establish strong engineering standards across system design, APIs, microservices, databases, and distributed systems.

Quality Assurance & Release Governance

- Own the overall QA strategy, testing standards, and release governance framework.

- Ensure comprehensive testing of product releases, integrations, interfaces, APIs, and custom functionality.

- Drive automated testing initiatives across engineering teams.

- Establish release-readiness criteria, documentation standards, and quality metrics.

- Ensure production releases meet performance, security, reliability, and compliance requirements.

Team Leadership & People Development

- Build, mentor, and retain a high-performing R&D organisation comprising AI Engineers, ML Scientists, Software Developers,

Product Engineers, QA professionals, and Platform Engineers.

- Set clear objectives, performance expectations, and accountability frameworks.

- Foster a culture of innovation, experimentation, curiosity, collaboration, and technical excellence.

- Lead hiring, performance reviews, career development, capability building, and succession planning.

- Coach senior technical leaders and develop the next level of engineering and R&D leadership.

- Champion organisational values and a culture of continuous improvement.

Stakeholder & Cross-functional Collaboration

- Partner with Product Management to define product vision, priorities, and roadmap direction.

- Collaborate with Engineering, Design, Data, DevOps, Sales, and customer-facing teams to deliver integrated solutions.

- Communicate R&D strategy, technical trade-offs, risks, progress, and investment requirements to executive and non-technical

stakeholders.

- Participate in business review meetings and provide updates on roadmap execution, R&D performance, AI-driven efficiency gains,

and strategic initiatives.

- Engage with academic institutions, technology vendors, consultants, and strategic partners where required.

- Support go-to-market teams with technical inputs, product positioning, demonstrations, and customer discussions.

Operational Excellence

- Own project planning, budgets, resource allocation, timelines, and delivery governance for R&D initiatives.

- Define and track KPIs covering research outcomes, engineering productivity, delivery predictability, product quality, platform

reliability, and team performance.

- Establish MLOps practices, model monitoring, experimentation frameworks, and reproducibility standards.

- Manage intellectual property, patents, technical documentation, and knowledge repositories.

- Ensure compliance with applicable regulatory, information security, privacy, governance, and operational standards.

- Drive continuous improvement across engineering processes, tools, architecture, and team structures.

DESIRED CANDIDATE PROFILE

Required Qualifications & Experience

- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Electrical Engineering, or a related

discipline.

- A Ph.D. in a relevant discipline would be an added advantage.

- 15-18 years of overall experience in Software Engineering, Product Engineering, Research and Development, or related technology functions.

- Minimum 5 years of hands-on experience in Artificial Intelligence and Machine Learning.

- Minimum 4 years of experience in a senior managerial, engineering leadership, or technical leadership position.

- Proven track record of taking AI/ML products from concept and experimentation to scalable production deployment.

- Demonstrated experience leading and growing multidisciplinary technical teams.

- Strong experience managing product roadmaps, engineering delivery, budgets, resources, and senior stakeholders.

- Strong product orientation with the ability to balance research ambition, technical feasibility, customer value, and commercial

priorities.

Technical Expertise

- Strong programming expertise in Python.

- Working knowledge of Java, Go, C++, or TypeScript would be desirable.

- Hands-on experience with ML and Deep Learning frameworks such as:

- PyTorch

- TensorFlow

- Hugging Face Transformers

- scikit-learn

- Practical experience with:

- Large Language Models

- Generative AI

- Retrieval-Augmented Generation

- Fine-tuning

- Prompt Engineering

- AI Agents and Agentic Frameworks

- Natural Language Processing

- Computer Vision

Strong understanding of MLOps tools and practices, including:

- MLflow

- Kubeflow

- Apache Airflow

- Weights & Biases

- CI/CD for Machine Learning

- Model Monitoring and Governance

- Experience deploying AI workloads on AWS, GCP, or Microsoft Azure.

- Exposure to GPU-based infrastructure and scalable AI compute environments.

- Strong foundation in software engineering principles, system design, APIs, microservices, databases, distributed systems, and

platform architecture.

- Understanding of platform engineering, DevOps, release automation, security, reliability, and production operations.

Preferred Qualifications

- Experience developing products for regulated or enterprise domains suchs as Healthcare, Financial Services, Enterprise SaaS, or

similar industries.

- Experience establishing or scaling an R&D function from the ground up.

- Contributions to open-source AI projects, peer-reviewed research publications, or granted patents.

- Exposure to Responsible AI practices covering fairness, explainability, privacy, governance, and model risk.

- Experience working with globally distributed teams.

- Strong exposure to Agile and Scrum-based delivery models.

- Prior experience working closely with Product Management, customer-facing teams, and executive leadership.

- Candidates currently working as Senior Manager, Associate Director, Head of AI, Head of R&D, Head of Machine Learning, or a

similar leadership role will be preferred.

KEY SKILLS

- Research & Development Leadership

- Artificial Intelligence

- Machine Learning

- Deep Learning

- Generative AI

- Large Language Models

- Retrieval-Augmented Generation

- Natural Language Processing

- Computer Vision

- AI Agents

- MLOps

- Python

- PyTorch

- TensorFlow

- Hugging Face

- Cloud Platforms - AWS / GCP / Azure

- GPU Infrastructure

- Product Engineering

- Product Lifecycle Management

- Product Roadmap Governance

- System Design

- APIs and Microservices

- Distributed Systems

- Platform Engineering

- CI/CD

- QA and Release Governance

- Technical Strategy

- Engineering Delivery

- Team Building and Mentoring

- Stakeholder Management

- Budget and Resource Management

- R&D Organisation Scaling

- Cross-functional Collaboration

WHAT THE COMPANY OFFERS:

- Competitive compensation with performance-linked incentives.

- Comprehensive health insurance coverage for employees and dependants.

- Access to modern AI tooling and GPU computing infrastructure.

- Dedicated learning and development budget for certifications, conferences, and professional courses.

- Opportunity to shape the organisations AI, product engineering, and R&D strategy.

- Exposure to global teams, enterprise customers, and large-scale technology initiatives.

- Long-term career opportunities within the wider Harris Computer / Harris International Group.