3 months ago
London, United KingdomStaff+
Responsibilities
- Own technical solution design and architecture decisions for enterprise Agentic AI and GenAI projects.
- Design, develop, deploy, and lead end-to-end delivery of production-grade AI solutions.
- Build agentic workflows with tool use, orchestration, routing, memory, and multi-agent patterns.
- Implement evaluation frameworks for quality, grounding, task success, safety, latency, and cost.
- Ensure solutions meet scalability, reliability, security, maintainability, observability, governance, and cost-optimization standards.
- Lead implementation against agreed architecture and quality standards through deployment and handover.
- Mentor junior team members and guide engineering standards and best practices.
- Collaborate with cross-functional teams and manage technical stakeholder and client conversations.
- Support or lead pre-sales activities including solution shaping, technical estimations, demos, proposals, and client discussions.
Requirements
- Hands-on experience building AI solutions 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 model reliability patterns.
- Experience deploying AI solutions into production with attention to cost optimization, scalability, observability, security, and governance.
- Experience with M365, Copilot Studio, Azure AI Foundry, and Microsoft Agent Framework.
- Proficiency in Python and production-quality software engineering practices.
- Strong understanding of software engineering principles, architecture patterns, and delivery practices.
- Experience developing APIs with FastAPI, Flask, or Django.
- Knowledge of Docker, containerized deployments, and cloud-native delivery patterns.
- Experience building, deploying, and evaluating multi-agent AI solutions, agent orchestration patterns, RAG architectures, and enterprise integrations is preferred.
- Knowledge of MCP, A2A, and agent interoperability patterns is preferred.
- Ability to balance innovation with delivery risk, cost, security, and production-readiness considerations.
- Bachelor’s degree in Computer Science, Data Science, or a related field.
- Microsoft certification such as Azure AI Apps and Agents Developer Associate or Agentic AI Business Solutions Architect.
Benefits
- At least 80 hours of annual training and paid certifications.
- Access to technical and skilled resources globally.
- Opportunities to collaborate with Microsoft technical experts and develop expertise through learning and problem-solving.
- Inclusive and diverse culture with mentoring, supportive collaboration, and opportunities for ambitious growth.
Categories
About Avanade
Avanade is the world’s leading expert on Microsoft. Trusted by over 7,000 clients worldwide, we deliver AI-driven solutions that unlock the full potential of people and technology, optimize operations, foster innovation and drive growth. As Microsoft’s Global SI Partner we combine global scale with local expertise in AI, cloud, data analytics, cybersecurity, and ERP to design solutions that prioritize people and drive meaningful impact. We champion diversity, inclusion, and sustainability, ensuring our work benefits society and business.