Senior Delivery Consultant AI - Enterprises, AWS Professional Services

Job :  | AWS EMEA SARL (UK Branch)

The Amazon Web Services Professional Services (Pro Serve) team is seeking a Senior Delivery Consultant specialising in AI/ML and generative AI to join our Data & AI practice. In this role, you will lead the technical direction and delivery of complex enterprise AI engagements, working across multiple work streams and helping customers establish repeatable capabilities for adopting AI responsibly at scale.

This is a senior, hands‑on individual‑contributor role. You will move between strategic and implementation detail: shaping solutions and delivery roadmaps around customer use cases with senior stakeholders, making architecture and engineering trade‑offs, reviewing code and evaluation evidence, and removing technical blockers for delivery teams. You will operate effectively when requirements are incomplete, making evidence‑based recommendations and creating clarity for customer, AWS, and partner teams.

Beyond individual solutions, you will help customers address the wider conditions required for sustained value from AI, including data readiness, platform architecture, security, governance, operating models, adoption, and value measurement. You will also strengthen the Data & AI practice through mentoring, technical standards, reusable assets, and feedback from customer delivery.

The AWS Professional Services organisation is a global team of experts that helps customers realise their desired business outcomes using AWS. We work with customer teams and the AWS Partner Network (APN) to execute enterprise cloud and AI transformation initiatives.

• Translate customer use cases and business objectives into well-scoped AI solutions with measurable success criteria, technical requirements, and an iterative delivery plan.
• Design and implement production AI solutions on AWS, including the application, data, integration, security, and operational components required to run them reliably.
• Select and evaluate appropriate AI approaches, which may include traditional ML, large language models, retrieval, model adaptation (fine tuning, continuous pre‑training), tool use, or agentic workflows.
• Establish evaluation and responsible AI controls covering solution quality, safety, privacy, security, latency, reliability, and cost.
• Diagnose technical issues across models, applications, data, and infrastructure, and communicate trade‑offs clearly to customer stakeholders.
• Work with customer and partner teams to integrate solutions into existing workflows and complete documentation, knowledge transfer, and operational handover.
• Use AI‑assisted development practices, and contribute reusable assets and lessons to the Data & AI practice.

A typical day may include working with a customer team to turn an agreed use case into a detailed solution design and delivery backlog. You might review evaluation results from an AI application, investigate a quality, security, latency, or cost issue, and implement and test an improvement. Later, you may run a technical workshop to resolve data or integration constraints, pair with a customer engineer on code, or review an architecture decision with security and platform teams.

You will regularly communicate progress, risks, and technical trade‑offs to business and technical stakeholders. As delivery moves towards production, you will help establish monitoring and operational processes, complete documentation and knowledge transfer, and ensure the customer team can operate and extend the solution after the engagement.

Amazon values diverse experiences and encourages candidates to apply even if they do not meet every preferred…