TL Consulting Group is a professional services organisation specialised in driving transformational uplift through intelligent, automated solutions across infrastructure, application, and data layers. Our model is aligned to Cloud Native architecture, DevSecOps, and modern data platforms, leveraging strategic partnerships with Microsoft and leading AI providers to deliver next‑generation engineering capabilities. POSITION PURPOSE The AI Technical Lead, Azure AI & Agentic Engineering leads the design, development, and delivery of AI‑powered applications and agentic systems, with a strong focus on Azure AI Foundry, GitHub Copilot, and enterprise‑scale LLM integration. This is a hands‑on leadership role that blends deep technical expertise with delivery ownership. The role is centred on building agent‑based solutions, orchestrating AI workflows, and rapidly developing PoCs and MVPs that deliver measurable business value. A key responsibility is enabling organisations to adopt agentic AI patterns by integrating large language models such as OpenAI, Claude, and Gemini into production‑grade applications, developer ecosystems, and automation pipelines. The ideal candidate is a strong software engineering leader who can guide high‑performing teams through the transition to AI‑enabled application development and modern engineering workflows. KEY RESPONSIBILITIES Agentic AI & Application Engineering Build and deploy AI applications using Azure AI Foundry and related Azure services. Lead the design and implementation of agentic AI systems. Develop Retrieval‑Augmented Generation (RAG) solutions using structured and unstructured enterprise data. Design and implement agent orchestration patterns. Rapidly prototype and deliver PoCs and MVPs to validate AI use cases and business value. AI Engineering & Developer Productivity Lead enterprise adoption and optimisation of GitHub Copilot and AI‑assisted development practices. Embed AI into engineering workflows, including: Code generation, review, and refactoring Test automation and documentation generation Developer knowledge assistants and copilots Internal tools and automation pipelines CI/CD and DevSecOps workflows Implement Model Context Protocol (MCP) and advanced tool integration patterns where applicable. Technical Leadership & Delivery Act as technical lead across AI engineering engagements. Own solution design, architecture, and hands‑on delivery of AI solutions. Guide engineering teams on best practices for: LLM integration and orchestration Scalability, performance, and reliability Ensure alignment to security, governance, and responsible AI frameworks. Provide mentorship and technical oversight to engineers and consultants. Client Engagement & Innovation Work directly with clients to shape and refine AI use cases and solution approaches. Translate business problems into agentic AI workflows and technical solutions. Lead workshops, ideation sessions, and rapid prototyping engagements. Present solution designs, demos, and PoCs to both technical and executive stakeholders. Practice Contribution Develop reusable agent frameworks, accelerators, and reference architectures. #J-18808-Ljbffr