AI Technical Delivery Lead

Location: UK/Hybrid

Contract type: 6 months - Hybrid with strong possibility of extension

Role Purpose

The Technical Service Delivery Lead sits at the heart of the Process Transformation AI development team. This is a hands-on technical leadership role: The postholder translates product requirements into detailed low-level designs (LLDs), leads a team of AI developers day-to-day, and is personally accountable for the quality, reliability, and timely delivery of AI solutions built on AWS and agentic frameworks. The role demands deep engineering capability alongside the communication skills to collaborate effectively with Product Owners, business stakeholders, and cross-functional delivery teams.

Key responsibilities

Technical Leadership & Team Management

•    Lead the day-to-day technical work of an AI development team across multiple concurrent AI projects.
•    Set and enforce engineering standards including version control practices (Git/CodeCommit), code review processes, documentation (markdowns), and branching strategies.
•    Mentor developers, conduct technical reviews, and ensure the team maintains high engineering

hygiene throughout the delivery lifecycle.

•    Manage workload distribution, unblock technical dependencies, and escalate risks proactively.

Design & Requirements Translation

•    Produce detailed Low-Level Designs (LLDs) from product requirements and business use cases, covering data flows, service interactions, agent architectures, and API contracts.
•    Decompose LLDs into clearly scoped, independently deliverable technical build tasks for the development team.
•    Maintain design documentation throughout the project lifecycle, ensuring LLDs remain current as requirements evolve.
•    Validate that delivered solutions conform to the agreed LLD and meet acceptance criteria before release.

AWS Platform & Agentic AI Delivery

•    Lead engineering delivery using core AWS developer services: Boto3, AWS Bedrock AgentCore, CloudWatch, AWS CodeCommit, ECS/ECR, and related tooling.
•    Design and implement agentic AI workflows using frameworks including LangGraph and CrewAI, including multi-agent coordination, tool integration, and memory management.
•    Oversee containerised deployment pipelines (ECS/ECR), ensuring robust CI/CD pipelines with appropriate environment controls.
•    Monitor deployed solutions using CloudWatch, define alerting strategies, and respond to operational issues.

Collaborative Code Development

•    Champion collaborative development practices including Git-based workflows, pull requests, code review standards, and commit discipline across the team.
•    Manage repositories across AWS CodeCommit and GitHub, including branching strategy, release tagging, and access governance.
•    Promote and enforce Test Driven Development (TDD) practices — ensuring unit tests, integration tests, and coverage standards are embedded from the start of each build task.
•    Integrate automated testing into CI/CD pipelines to maintain continuous quality assurance throughout delivery.

Stakeholder Collaboration & Delivery Governance

•    Work closely with Product Owners to refine requirements, clarify acceptance criteria, and ensure technical feasibility is assessed early.
•    Participate in sprint planning, backlog refinement, and retrospectives, providing technical estimates and identifying dependencies.
•    Communicate delivery status, risks, and technical decisions clearly to both technical and non-technical stakeholders.
•    Contribute to delivery governance including progress reporting, risk logging, and milestone tracking.

Skills and experience required

Team Leadership: Proven experience leading a team of software/AI developers across multiple AI projects, managing day-to-day technical delivery and engineering quality.

LLD Creation: Demonstrated ability to produce Low-Level Designs from business and product requirements, and to translate these into actionable build tasks.

AWS Developer Services: Hands-on experience with Boto3, AWS Bedrock AgentCore, CloudWatch, AWS CodeCommit, and container deployment via ECS/ECR.

Agentic Frameworks: Practical experience building agentic AI systems using LangGraph and/or CrewAI in a production or near-production context.

Collaborative Code Development: Strong Git discipline including branching, pull requests, code review, and repository management across GitHub and/or AWS CodeCommit.

Test Driven Development: Embedded TDD practices within a development team — writing tests before code, maintaining coverage thresholds, and integrating tests into CI/CD pipelines.

Stakeholder Collaboration: Experience working directly with Product Owners and business stakeholders in an Agile environment to shape and deliver outcomes.