AI Engineering Lead/Architect

Job Description What You Will Do Delivery & Programme Leadership

• Own end-to-end delivery of a $10M+ engineering portfolio across clients — on time, on budget, and to quality bar.
• Lead platform build, modernisation, and custom application programmes natively on cloud, spanning .NET Full-Stack, Java Distributed Systems, Python stack etc.
• Set and enforce engineering standards: architecture guardrails, code quality, DevSecOps, and release cadence across multi-team engagements.
• Manage programme risk proactively — escalate early, resolve decisively, and keep clients informed throughout. AI-Driven Engineering Acceleration
• Embed AI tooling across the SDLC — from AI-assisted requirements and design through to automated testing, code generation, and incident response.
• Architect and operationalise agentic systems and workflows that reduce manual toil, accelerate delivery cycles, and improve output quality.
• Quantify the impact of AI adoption: establish baselines, track velocity and quality metrics, and present measurable efficiency gains to clients and leadership.
• Stay ahead of the AI tooling curve; evaluate and pilot emerging platforms (LLM orchestration, RAG pipelines, AI code assistants). Portfolio & Revenue Growth
• Carry full P&L accountability for the portfolio — margin, revenue, forecasting, and commercial hygiene.
• Partner with practice, consulting, and client partner leaders to identify expansion opportunities within existing accounts and shape new pursuit strategies.
• Translate delivery track record into growth narrative — contribute to proposals, solution designs, and client presentations that differentiate on execution credibility. Client & Stakeholder Engagement
• Serve as the senior delivery point-of-contact for clients — build trust-based relationships at CTO/CIO/VP level.
• Facilitate governance forums (steering committees, QBRs, escalation calls) with clarity and confidence.
• Align internal stakeholders — practice heads, resource managers, people leaders — to programme needs without bureaucratic drag. People & Capability Development
• Lead, mentor, and grow a high-performing engineering organisation; foster a culture of ownership and continuous improvement.
• Champion individual upskilling — create structured learning pathways around AI, cloud, and modern engineering practices.
• Spot and develop next-generation delivery leaders from within the team.