Description

Lead large-scale engineering portfolios and deliver AI-driven solutions across client engagements.

This role is on-site.

Responsibilities

• Own end-to-end delivery of engineering portfolios, ensuring on-time, on-budget execution and quality standards.
• Set and enforce engineering standards including architecture guardrails, DevSecOps, and release cadence.
• Embed AI tooling across the SDLC, from requirements and design to automated testing and code generation.
• Architect and operationalise agentic systems and workflows to reduce manual toil and accelerate delivery.
• Carry full P&L accountability for margin, revenue, forecasting, and commercial hygiene.

Required Skills

• 17+ years of engineering experience with a Bachelor's degree.
• Strong background in Cloud Platforms: Azure, AWS, or GCP; Infrastructure as Code; CI/CD.
• Backend Engineering: .NET Full-Stack (C#, ASP.NET Core) and/or Java (Spring Boot, Microservices).
• Distributed Systems experience with Kafka and Kubernetes.
• Python Stack proficiency: FastAPI, Django/Flask, pandas, NumPy for data pipelines and AI/ML integrations.
• AI & Automation: Agentic AI systems, LLM orchestration, RAG pipelines, multi-agent workflows.
• Familiarity with AI coding assistants (GitHub Copilot, Claude, Cursor).

Preferred Skills

• Experience serving as the senior delivery point-of-contact for clients at CTO/CIO/VP level.

Key Skills

Education

Bachelor's degree