Description

Key Responsibilities

• Own end-to-end delivery of large-scale engineering portfolios across clients — on time, on budget, and to quality bar
• Set and enforce engineering standards: architecture guardrails, code quality, DevSecOps, and release cadence across multi-team engagements
• 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 and accelerate delivery cycles
• Carry full P&L accountability — margin, revenue, forecasting, and commercial hygiene
• Serve as the senior delivery point-of-contact for clients at CTO/CIO/VP level

Required Skills

• Cloud Platforms: Azure, AWS, or GCP; Infrastructure as Code, CI/CD, container orchestration, observability
• Backend Engineering: .NET Full-Stack (C#, ASP.NET Core) and/or Java Distributed Systems (Spring Boot, Microservices, Kafka, Kubernetes)
• Python Stack: FastAPI, Django/Flask, pandas, NumPy — for data pipelines, AI/ML integrations, and automation
• AI & Automation: Agentic AI systems, LLM orchestration, RAG pipelines, multi-agent workflows, GitHub Copilot, Claude, Cursor

Key Skills

Education

Bachelor's degree