Summary
As a Forward Deployed Engineer at Avanade, you will embed directly with clients to understand their business, processes and priorities, uncover high-value opportunities for AI, and rapidly turn ideas into working solutions. You will combine business acumen, deep technical expertise and a pragmatic consulting approach to help clients move from ambition to measurable outcomes at speed.
This is a hands-on, client-facing role at the intersection of AI strategy, solution architecture and engineering. You will lead discovery, create and prioritise AI opportunity backlogs, establish the governance and structures needed to support responsible adoption, educate client teams, and architect, build and demonstrate production-minded prototypes using the latest Microsoft technologies.
Role Responsibilities
Client Discovery and Opportunity Shaping
- Embed with client teams to understand their organisation, business processes, technology landscape and strategic priorities.
- Lead discovery, ideation and design workshops with business and technology stakeholders.
- Identify and assess opportunities where AI, agents and automation can deliver meaningful business value.
- Translate ambiguous business challenges into clear use cases, solution hypotheses and actionable technical requirements.
- Create, structure and prioritise AI opportunity backlogs, balancing value, feasibility, risk and time to impact.
- Develop pragmatic roadmaps, estimates and recommendations that help clients move from experimentation into scaled delivery.
High-Velocity Solution Engineering
- Architect, build and rapidly iterate AI agents, prototypes and proofs of value using Azure AI Foundry, Azure OpenAI, Microsoft Copilot Studio and Power Platform.
- Own solutions from initial concept through technical design, build, demonstration, evaluation and transition into production delivery.
- Apply high-velocity engineering approaches to test assumptions quickly, learn from users and evidence value early.
- Integrate AI solutions with enterprise systems, data sources, APIs and workflows using Microsoft and Azure services.
- Apply strong engineering practices across source control, testing, evaluation, deployment, monitoring, security and operational readiness.
- Ensure solutions are scalable, maintainable and aligned with enterprise architecture, security, responsible AI and governance requirements.
Client Enablement, Governance and Adoption
- Help clients establish practical AI governance, delivery structures and ways of working that support responsible experimentation and scale.
- Educate client stakeholders and delivery teams on agentic AI capabilities, limitations, patterns and good engineering practices.
- Facilitate solution demonstrations and playback sessions, using feedback to refine priorities and accelerate adoption.
- Coach client teams so that knowledge and capability are transferred throughout the engagement.
- Build trusted relationships across business and technology teams, communicating technical concepts, trade-offs and value in clear language.
Avanade Capability and Growth
- Support pre-sales activities through discovery, solution shaping, estimation, demonstrations and proof-of-concept development.
- Contribute reusable assets, patterns, accelerators and lessons learned to Avanade's Data & AI communities.
- Stay current with Microsoft's AI roadmap and emerging engineering approaches, translating developments into practical client applications.
- Collaborate with architects, engineers, industry specialists and alliance teams to bring the best of Avanade and Microsoft to clients.
- Mentor colleagues and promote a culture of curiosity, pace, quality and accountable delivery.