Difinity Digital is a Data and AI consulting firm delivering solutions across artificial intelligence, data and analytics, and digital engineering for clients in the UAE and Europe, alongside a portfolio of proprietary products.

The Engineering Head holds complete ownership of the engineering function. The role carries accountability for technical strategy, delivery governance, engineering capability and organisational structure, in addition to the architecture and quality of every solution the company builds and deploys.

The position combines functional leadership with continued technical depth. The Engineering Head is expected to set direction, build the team and govern delivery, while remaining sufficiently hands-on in architecture and technical review to hold authority over engineering decisions.

EXPERIENCE: 10+ years

2. Key Responsibilities

Engineering Strategy and Function Ownership

1. Define the technical strategy for the engineering function across AI, data and analytics, and product engineering.
2. Establish the technology roadmap, platform standards and architectural principles adopted across the organisation.
3. Build and maintain the engineering capability plan, including skill development, team structure and workforce planning.
4. Manage relationships with technology partners and platform vendors and evaluate new tooling and platforms for adoption.
5. Own engineering budgets, tooling investment and infrastructure cost governance.

Delivery Governance

1. Hold accountability for technical delivery across all client engagements and internal product development.
2. Establish delivery methodology, engineering standards, quality gates and release governance.
3. Oversee resource allocation, utilisation and capacity planning across concurrent engagements.
4. Monitor delivery health, manage technical and schedule risk, and own resolution of technical escalations.
5. Report engineering performance, risk and capacity to the Director.

Solution Architecture and Technical Requirements

1. Own solution architecture and data architecture standards across the organisation.
2. Approve the technical approach,



feasibility position and effort estimation for new engagements.
3. Contribute directly to architecture design for complex, high-risk or strategically significant engagements.
4. Review and approve the technical content of client proposals and statements of work.

Technical Quality and Governance

1. Define and enforce code review, design review and security review standards.
2. Maintain final approval authority on architecture decisions and technical debt trade-offs.
3. Drive the development of reusable frameworks, accelerators and reference implementations.

Organisational and People Leadership

1. Lead, structure and scale the engineering organisation across all technical disciplines.
2. Own technical hiring, including role definition, assessment frameworks and interview panels.
3. Establish performance management, career progression paths and technical competency frameworks.
4. Mentor senior engineers and develop the next layer of technical leadership.

Deployment, Security and Compliance

1. Ensure all solutions are deployed securely with appropriate access controls, data privacy measures and regulatory compliance.
2. Define governance for AI systems including model evaluation, guardrails, monitoring, failure handling and cost control.
3. Own production readiness criteria and post-deployment support standards.

Client and Commercial Engagement

1. Represent the engineering function in client engagements requiring senior technical authority, including solution workshops, architecture presentations and escalation management.
2. Support pre-sales through technical validation, solution design and credibility in client-facing technical discussions.

3. Skills and Experience





Candidates are assessed on demonstrated capability and delivery track record rather than years of experience. Depth in every discipline is not expected.

1. Proven ownership of engineering delivery for a team or function, with accountability for architecture and quality outcomes.
2. Track record of taking production systems from requirement through to live deployment and ongoing support.
3. Strong, demonstrable expertise in at least one of the following areas: artificial intelligence, data and analytics, or product engineering.
4. Applied experience in artificial intelligence covering machine learning, computer vision or natural language processing, and generative AI including large language model applications and retrieval augmented generation.
5. Applied experience in data and analytics covering data engineering, pipeline design, warehouse or lakehouse architecture, data modelling, governance, and business intelligence.
6. Applied experience in product engineering covering application and product engineering, API and backend service design, enterprise system integration, cloud infrastructure and DevOps.
7. Sufficient working knowledge of the disciplines outside the primary area of expertise to conduct architecture review, validate estimates, assess technical risk and assess technical candidates.
8. Working knowledge of cloud deployment practice, CI/CD, security, access control and data privacy.
9. Understanding of AI governance including model evaluation, guardrails, monitoring and cost control.
10. Experience building, structuring and developing engineering teams.
11. Delivery experience in a consulting, professional services or client-facing product setting.
12. Ability to present and defend technical positions to executive, client and engineering audiences.
13. Experience in offshore delivery models serving international clients is desirable.
14. Commercial understanding of utilisation, margin and estimation discipline in a services business is desirable.
15. Bachelor's degree in Computer Science, Engineering, Information Technology or a related discipline. Postgraduate qualification desirable.

📌 Engineering Lead (Kochi)
🏢 Difinity Digital
📍 Kochi