Lead Agentic AI Engineer

Avanade; Greater London; On-site; GBP 90,000 - 150,000; Full time

Benefits offered by this job

Training & certifications

Global access to technical resources

Collaboration with Microsoft experts

Career development opportunities

Job summary

Avanade is seeking a highly skilled Lead Agentic AI Engineer to drive end-to-end design, development, and deployment of production-grade generative AI and agentic solutions using Microsoft technologies. You will lead architectural decisions, mentor engineers, and collaborate with cross-functional teams to deliver scalable, secure AI systems.

Required skills include hands-on experience with LLMs, agentic AI design, prompt engineering, and production deployments within the Microsoft GenAI

Qualifications

• Hands-on experience with LLMs such as OpenAI GPT, Claude, Gemini or Mistral.
• Experience designing and building agentic AI solutions, including tool use, workflow orchestration, routing, memory, and multi-agent patterns.
• Expertise in prompt engineering, structured outputs, and reliability patterns to optimise model performance.
• Ability to implement evaluation frameworks for quality, grounding, task success, safety, latency, and cost.
• Experience deploying AI solutions into production with focus on cost optimisation, scalability, observability, security, and governance.
• Experienced in using Microsoft GenAI ecosystem, including M365, Copilot Studio, Azure AI Foundry, and Microsoft Agent Framework.
• Proficient in Python and production-quality code practices.
• Strong understanding of software engineering principles, architecture patterns, and delivery best practices.
• Experience with API development using frameworks such as FastAPI, Flask, or Django.
• Knowledge of Docker, containerised deployments, CI/CD, and cloud-native delivery patterns.

Responsibilities

• Take ownership of technical solution design and architecture decisions, bringing clarity from ambiguous client requirements.
• Act as the technical lead on projects, guiding implementation approach, engineering standards, and best practices.
• Design, develop, and deploy Agentic AI and GenAI solutions in enterprise environments.
• Lead end-to-end solution delivery, from discovery and design through implementation, deployment, and handover.
• Make clear technical design decisions that support scalability, reliability, security, and maintainability.
• Lead and mentor junior team members, helping them deliver high-quality outcomes and grow their technical capability.
• Collaborate effectively with cross-functional teams in agile environments.
• Manage technical stakeholders and client conversations, translating business needs into practical AI solution designs.
• Support or lead pre-sales activities, including solution shaping, technical estimations, demos, proposals, and client discussions.
• Lead implementation during delivery, ensuring the proposed solution is built to the agreed architecture and quality standards.

Skills

LLMs

Agentic AI

Prompt engineering

Evaluation frameworks

Production deployment

Microsoft GenAI ecosystem

Python

Software engineering

API development

Docker

Education

Bachelor's degree in CS/Data Science

Microsoft certifications (Azure AI Apps and Agents Developer Associate / Agentic AI Business Solutions Architect)

Tools

Docker

FastAPI

Flask

Django

Azure AI Foundry

Microsoft Agent Framework

Copilot Studio

M365

Job description

Lead Agentic AI Engineer

We are seeking a highly skilled and innovative Lead Agentic AI Engineer to join our team and drive the design, development, and deployment of production‑grade generative AI and agentic solutions using Microsoft technologies.

This role is ideal for a technically strong engineer who has hands‑on experience building AI solutions, orchestrating agentic workflows, implementing evaluation frameworks, and deploying solutions into secure, scalable, and cost‑optimised production environments using platforms such as Azure AI Foundry, Microsoft Agent Framework, and Copilot Studio.

Key Responsibilities

• Take ownership of technical solution design and architecture decisions, bringing clarity from ambiguous client requirements
• Act as the technical lead on projects, guiding implementation approach, engineering standards, and best practices
• Design, develop, and deploy Agentic AI and GenAI solutions in enterprise environments
• Lead end‑to‑end solution delivery, from discovery and design through implementation, deployment, and handover
• Make clear technical design decisions that support scalability, reliability, security, and maintainability
• Lead and mentor junior team members, helping them deliver high‑quality outcomes and grow their technical capability
• Collaborate effectively with cross‑functional teams in agile environments
• Manage technical stakeholders and client conversations, translating business needs into practical AI solution designs
• Support or lead pre‑sales activities, including solution shaping, technical estimations, demos, proposals, and client discussions
• Lead implementation during delivery, ensuring the proposed solution is built to the agreed architecture and quality standards

Qualifications

• Hands‑on experience with LLMs such as OpenAI GPT, Claude, Gemini or Mistral
• Experience designing and building agentic AI solutions, including tool use, workflow orchestration, routing, memory, and multi‑agent patterns
• Expertise in prompt engineering, structured outputs, and reliability patterns to optimise model performance
• Ability to implement evaluation frameworks for quality, grounding, task success, safety, latency, and cost
• Experience deploying AI solutions into production with focus on cost optimisation, scalability, observability, security, and governance
• Experienced in using Microsoft GenAI ecosystem, including M365, Copilot Studio, Azure AI Foundry, and Microsoft Agent Framework
• Proficient in Python and production‑quality code practices
• Strong understanding of software engineering principles, architecture patterns, and delivery best practices
• Experience with API development using frameworks such as FastAPI, Flask, or Django
• Knowledge of Docker, containerised deployments, CI/CD, and cloud‑native delivery patterns

What Will Make You Stand Out

• Experience building, deploying, and evaluating multi‑agent AI solutions, agent orchestration patterns, RAG architectures, and enterprise integrations
• Knowledge of agent communication protocols and interoperability patterns, such as MCP and A2A
• Ability to balance innovation with practical delivery considerations, including risk, cost, security, and production readiness
• Confidence contributing to pre‑sales while also being able to lead implementation during delivery
• Curiosity and motivation to stay current with the latest advancements in GenAI, agentic AI, and AI engineering frameworks

Education & Certifications

• Bachelor’s degree in Computer Science, Data Science, or a related field
• Microsoft certified (e.g., Azure AI Apps and Agents Developer Associate or Agentic AI Business Solutions Architect)

Benefits

• Opportunity to work for Microsoft’s Global Alliance Partner of the Year (14 years in a row), with exceptional development and training (minimum 80 hours per year for training and paid certifications)
• Real‑time access to technical and skilled resources globally
• Collaborate with some of the brightest Microsoft minds
• Build your expertise, solve problems, learn, and develop