Description :

The ideal candidate should possess exceptional leadership skills, a deep understanding of technology, AI-driven systems, and modern tech infrastructure, along with the ability to drive complex product development cycles.

As the Head of Engineering, you will serve as a strategic partner to the management team, aligning technology and AI initiatives with business goals and future company endeavors. The role requires a strong background in Artificial Intelligence, Machine Learning adoption, intelligent automation, and AI-led product transformation within scalable platforms.

Key Responsibilities :

Technology Leadership :

- Provide strategic leadership and oversight for the technology and AI engineering teams, ensuring the delivery of innovative, AI-enabled, and tailor-made project solutions.

- Own the engineering deliverables and P&L for the tech function, driving the product roadmap, AI adoption strategy, product evolution, and scalable architecture.

- Identify, evaluate, and implement emerging AI technologies and intelligent automation solutions that enhance competitive edge in the healthcare fintech and procurement sectors.

- Lead the integration of AI/ML capabilities into products, workflows, analytics platforms, and customer-facing solutions.

Product Development & Transformation :

- Oversee the complete product life cycle, managing front-end, back-end, cloud, and AI- powered solution development to deliver high-quality, scalable products.

- Develop and implement scalable, secure, and AI-ready product architectures supporting multiple product lines.

- Drive digital transformation initiatives by leveraging cloud technologies (AWS, Azure), Generative AI, predictive analytics, and data-driven decision-making frameworks.

- Collaborate with cross-functional teams to incorporate AI-driven insights, automation, and intelligent workflows into core business operations.

Team Management & Development :

- Build, mentor, and scale a high-performing technology and AI engineering team, fostering a culture of innovation, collaboration, experimentation, and continuous learning.

- Ensure teams are equipped with modern AI tools, frameworks, and engineering best practices to meet evolving business and technological demands.

- Drive AI capability building across engineering teams through mentorship, hiring strategy, and continuous upskilling initiatives.

- Adhere to allocated budgets for resource planning while aligning with the Annual Operating Plan (AOP).

Technical Oversight :

- Ensure robust security, compliance, governance, and risk management practices across all technology and AI platforms.

- Establish best practices for responsible AI adoption, data privacy, model governance, and ethical AI implementation.

- Maintain deep expertise in industry trends, emerging AI technologies, cloud platforms, and modern engineering practices to guide long-term technology strategy.

Education & Qualifications :

- B.Tech/M.Tech in Computer Science, Information Technology, or a related field.

- Strong technical expertise with a deep understanding of software development, architecture, and engineering best practices.

Experience & Skills :

- 15+ years of experience in technology leadership roles, with significant exposure to AI-led product engineering and digital transformation initiatives.

- Proven track record of managing and scaling technology and AI teams in fast-paced environments.

- Extensive experience in front-end, back-end, cloud, and AI-enabled application development with a comprehensive understanding of the product life cycle.

- Hands-on experience with AI/ML technologies, Generative AI, intelligent automation, data platforms, and analytics-driven product ecosystems.

- Expertise in software architecture, cloud computing, DevOps, cybersecurity, and AI infrastructure management.

- Proficiency in modern programming languages, AI frameworks, cloud-native architectures, and technologies relevant to fintech and healthcare solutions.

- Strong understanding of data engineering, model deployment pipelines, MLOps, and scalable AI system implementation.