AI Technical Delivery Manager (Customer)

Job Role: AI Technical Delivery Manager (Customer)

Team: Song AI & Data - AI & Modelling Craft, UK&I

Location: London / Manchester

Career Level: Manager (L7)

We Are

Accenture Song accelerates growth and value for our clients through sustained customer relevance. Our capabilities span ideation to execution: growth, product and experience design; technology and experience platforms; creative, media and marketing strategy; and campaign, content and channel orchestration. With strong client relationships and deep industry expertise, we help our clients operate efficiently and sustainably through the unlimited potential of imagination, technology and intelligence.

Visit us at:https://www.accenture.com/gb-en/about/accenture-song-index

The Team

Within Accenture Song sits AI & Data, the practice that builds the data-led intelligence behind the customer work. Song AI & Data helps organisations unlock value from data, analytics and AI by creating more relevant, personalised and effective customer experiences. Our expertise spans customer insight, data strategy and platforms, advanced analytics, performance optimisation, and AI (including generative AI and agentic AI) transformation.

You will join the Song AI & Data UK practice, within the AI & Modelling Craft: a community of data scientists, AI engineers, modellers and solution architects focused on applying AI, machine learning and advanced analytics to solve customer and growth challenges. Our teams work across the full lifecycle, from identifying opportunities and designing solutions through to building, deploying and operating AI products that deliver measurable business value.

The Role

Generative AI is moving from experimentation into enterprise delivery, and the gap between a compelling demonstration and a production-ready solution remains significant. Solutions that succeed at scale must be reliable, secure, cost-effective and capable of delivering measurable business outcomes.

As an AI Technical Delivery Manager, you will be the hands-on technical lead for the delivery of customer AI and agentic solutions. You will lead a team of AI engineers and data scientists day to day, own the technical quality of what is built, review code and designs, and make sure the solution moves from proof of concept into a production service that runs reliably.

The role combines technical leadership, engineering quality and delivery accountability for your engagement.

You will make the day-to-day technical decisions that determine whether the solution works, performs and can be supported, and you will keep the delivery lead and client stakeholders informed about progress, risks and trade-offs.

You will work across customer-facing AI use cases including personalisation, customer decisioning, customer service agents, retrieval-augmented generation solutions and agentic workflows.

This is a technical role.

You will be expected to read and review code, understand how the models, prompts, retrieval and agent orchestration actually behave, and step in to unblock the team when needed. You will be leading engineers rather than doing all the engineering yourself, but you need to know the work well enough to set the standard, spot problems early and hold your own with experienced engineers and architects.

What You Will Do

• Lead the technical delivery of customer AI and agentic solutions, owning the day-to-day technical plan, task breakdown, sequencing and technical quality across the engineering team.

• Review code, prompts, retrieval pipelines, agent designs and evaluation results, giving clear feedback and making sure what is merged meets the agreed standards.

• Lead technical design within the engagement, covering model selection, retrieval-augmented generation, agentic workflows, evaluation frameworks, guardrails, scalability and cost, working with the solution architect where one is assigned.

• Identify technical and delivery risks early, including data quality issues, integration complexity, performance bottlenecks, cost overruns and operational readiness concerns, and raise them with the delivery lead together with options for addressing them.

• Set up and run the engineering practices the team works to, including code review, testing, evaluation, CI/CD, environment management, monitoring and release processes.

• Assess whether proofs of concept are ready to scale, clearly explaining what has been proven, what has not and what is required before production deployment.

• Work with client technical teams on integration, environments, data access, security and deployment, and explain technical progress, issues and trade-offs to client stakeholders in plain terms.

• Lead and develop a team of AI engineers and data scientists, allocating work, coaching individuals, running technical stand-ups and design reviews, and helping people grow.

• Contribute reusable code, patterns and delivery accelerators back to the AI & Modelling Craft, and share lessons learned from live delivery.

• Support solution shaping and estimation for new work, providing technical input on approach, effort, team composition and risks.

What We Are Looking For

Core Requirements

• Hands-on AI and agentic engineering. Experience building and shipping generative AI and agentic solutions into production, including retrieval-augmented generation, LLM-powered applications and agentic workflows. You have written the code yourself on at least some of these, and you understand how prompting, context management, retrieval, tool use, orchestration, evaluation and guardrails work in practice.

• AI and data science foundations. Good understanding of machine learning and data science alongside generative AI. You know how models are trained, evaluated and monitored, and you can tell when a problem calls for predictive modelling, optimisation, generative AI, agentic AI or a combination of approaches.

• Customer AI experience. Experience applying AI to customer growth, personalisation, marketing, commerce, sales or service challenges, and an understanding of how technical decisions affect customer and business outcomes.

• Engineering and platform skills. Strong Python and software engineering skills, with working knowledge of APIs, system integration, cloud platforms (Azure, AWS or GCP), containers, CI/CD, testing and production monitoring. You can review code properly, spot design and quality problems, and give feedback engineers can act on.

• Technical leadership of engineering teams. Experience leading a team of engineers or data scientists on a delivery, setting technical direction, running reviews, resolving technical issues and being accountable for the quality and timeliness of what the team produces.

• Delivery planning and estimation. Experience breaking technical work into a plan, estimating effort, tracking progress against it and adjusting when things change. You can distinguish what a proof of concept demonstrates from what is required for production.

• Stakeholder communication. Ability to explain technical progress, issues and trade-offs clearly to delivery leads, client technical teams and business stakeholders, and to raise problems as soon as they appear.

• Responsible AI and governance. Understanding of AI safety, evaluation, fairness, privacy, security and human oversight, and experience applying these in enterprise AI delivery.

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Nice to Have:

• Consulting experience. Experience working in a consulting or client-facing environment and contributing technical input to proposals, estimates or business cases.

What’s In It For You

Our Total Rewards consist of a competitive basic salary, annual performance bonus, opportunities to acquire equity and a wide range of health and wellbeing benefits. These include perks such as:

• 30 days of leave per year plus 3 extra volunteering days for charitable work of your choice.
• Family-friendly and flexible work policies.
• Attractive pension plan with financial wellbeing support and resources.
• Private healthcare insurance plan and Mental Wellbeing support.
• Employee Assistance Programme, Career Development and Counselling.
• A range of generous Parental Leave offerings.

SNGCR01

• Proven experience delivering Generative AI, RAG and agentic solutions.
• Strong Python, cloud and software engineering skills.
• Experience leading AI/data science teams and technical delivery.
• Strong stakeholder communication and Responsible AI knowledge.

About Accenture

Accenture is a leading global professional services company that helps the world’s leading businesses, governments and other organizations build their digital core, optimize their operations, accelerate revenue growth and enhance citizen services-creating tangible value at speed and scale. We are a talent- and innovation-led company with approximately 791,000 people serving clients in more than 120 countries. Technology is at the core of change today, and we are one of the world’s leaders in helping drive that change, with strong ecosystem relationships. We combine our strength in technology and leadership in cloud, data and AI with unmatched industry experience, functional expertise and global delivery capability. Our broad range of services, solutions and assets across Strategy & Consulting, Technology, Operations, Industry X and Song, together with our culture of shared success and commitment to creating 360° value, enable us to help our clients reinvent and build trusted, lasting relationships. We measure our success by the 360° value we create for our clients, each other, our shareholders, partners and communities.

Visit us atwww.accenture.com

Equal Employment Opportunity Statement

We believe that no one should be discriminated against because of their differences. All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, sexual orientation, gender identity or expression, marital status, citizenship status or any other basis as protected by applicable law. Our rich diversity makes us more innovative, more competitive, and more creative, which helps us better serve our clients and our communities.