Job objective Lead the implementation and scaling of AI-driven engineering tools, frameworks, and methodologies across the organisation. Drive adoption of AI-assisted development capabilities to improve productivity, software quality, and delivery velocity.
Responsibilities Strategic:Define the AI engineering enablement roadmap and ensure alignment with organisational digital strategy. Establish productivity and quality metrics to evaluate the impact of AI practices. Provide insights, recommendations, and ROI-driven justifications to senior leadership. Create enterprise-wide playbooks and guardrails for responsible and secure AI-assisted development. Guide long-term scaling strategy and integration of AI into standard engineering workflows. Financial:Define the financial impact of AI-assisted development through measurable productivity improvements and cost efficiencies. Conduct ROI analyses for pilots and scaled implementations. Ensure optimal utilisation of AI tooling investments and licensing. Support the business case for continued investment in AI tooling, training, and platform upgrades. Operational:Lead hands-on pilots with developer teams to evaluate and adopt AI-assisted coding, code review, testing, and quality assurance capabilities. Design and execute structured pilot plans with clear objectives, success criteria, and governance controls. Instrument engineering workflows to capture usage analytics, KPIs, and performance data. Create and maintain internal playbooks covering AI-assisted coding, test generation, refactoring, documentation, and quality automation. Curate reusable templates, examples, and engineering standards to support consistent adoption. Ensure seamless integration of AI capabilities with CI/CD pipelines, developer platforms, IDEs, Dev Ops toolchains, and security workflows. Collaborate with security, Dev Ops, and architecture teams to validate compliance, scalability, and performance. Troubleshoot technical issues and develop reference integrations. Execute rollout and onboarding plans following successful pilots, including adoption playbooks and enablement materials. Partner with training and documentation teams to support change enablement and developer upskilling. People:Ensure timely completion of PMR process Continuously share the knowledge and understanding of the technology industry and business trends Ensure active participation in employee engagement survey Mentor developers on effective use of AI tooling. Promote a culture of experimentation and continuous learning. Build partnerships with IT, Dev Ops, Security, and external vendors.
Required qualification & experience Bachelor’s degree in Computer Science, Software Engineering, or related field.7–10 years of experience in software engineering, Dev Ops, or platform engineering. Experience with AI-assisted development tools. Familiarity with MLOps concepts. Strong coaching and technical enablement skills.