AI Engineering Lead/Architect

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. B.E./B.Tech/M.E./M.Tech Computer Science, Electronics & Telecom Domain focus : Banking, Financial Services, Insurance, Retail & Consumer services What You Bring Experience & Background 10 15 years in software engineering with a significant portion in leadership roles managing multi-team, multi-million-dollar programmes. Hands-on track record of delivering platform build, legacy modernisation, and greenfield application programmes on cloud not just oversight, but technical depth you can draw on in client conversations. Technical Stack & Architecture .NET Full-Stack (C#, ASP.NET Core, Azure-native services) and/or Java Distributed Systems (Spring Boot, microservices, Kafka, Kubernetes) you can assess architecture quality, not just read status reports. Python stack experience (FastAPI, Django/Flask, pandas, NumPy) particularly for data pipelines, AI/ML integrations, and automation scripts. Cloud-native delivery on Azure, AWS, or GCP; Infrastructure as Code, CI/CD pipelines, container orchestration, and observability are second nature. Practical experience designing and deploying agentic AI systems LLM orchestration, tool-use patterns, retrieval-augmented generation, and multi-agent workflows in an enterprise context. AI & Automation Fluency Hands-on experience with enterprise AI coding and productivity tools GitHub Copilot / Claude (Anthropic), and / or Cursor applied meaningfully across design, development, review, and documentation phases of the SDLC. Understands where AI drives automation, acceleration, and efficiency within IT application landscapes and equally where it introduces risk that must be managed, especially in regulated domains. Ability to differentiate between AI hype and production-ready tooling; pragmatic evaluator of what to adopt, when, and how. Leadership & Commercial Acumen Proven P&L ownership at $10M+ scale comfortable with revenue forecasting, margin management, SOW negotiations, and change order governance. Excellent stakeholder management with both internal leaders and senior client executives; able to hold a room, manage difficult conversations, and build long-term advisory relationships. Growth mindset actively invests in own learning and models the same for the team. What Success Looks Like Outcome How We Measure It Delivery-led growth Year-on-year portfolio revenue growth; new SOWs sourced from existing accounts Execution excellence On-time, on-budget delivery rate; CSAT scores; reduction in critical defect leakage AI-driven efficiency Measurable reduction in manual effort and cycle times through AI tooling; documented ROI presented to clients People & capability Team retention, upskilling completion rates, and promotion pipeline health Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.