At a Glance
- Tasks: Lead AI delivery projects and shape transformational customer platform solutions.
- Company: Join Accenture Song, the world's largest tech-powered creative group.
- Benefits: Access to training, vibrant environment, and global network of specialists.
- Other info: Build a culture of learning and technical excellence while developing top talent.
- Why this job: Make a real impact in AI engineering and drive commercial growth.
- Qualifications: Extensive hands-on engineering experience and leadership in AI delivery.
The predicted salary is between 80000 - 100000 £ per year.
We are Accenture Song, the world’s largest tech‑powered creative group. For us, customer experience is not an add‑on; it’s foundational to who we are and how we empower our clients. As the world’s largest, most disruptive agency, we drive lasting growth for clients by helping them design, build, and run meaningful experiences that make people’s lives better, more productive, and more meaningful.
As an AI Delivery Tech Lead in Accenture Song Service, you will be accountable for Song’s most complex agentic programmes, shaping and delivering transformational customer platform solutions and driving commercial growth. If you’re looking for a challenging career working in a vibrant environment with access to training and a global network of specialists, this is the role for you.
The Service practice sits within Accenture Song. Our vision is to deliver iconic client outcomes by shaping exceptional agentic experiences that deliver cost transformation and drive growth. We focus on:
- Reinventing customer service across physical, digital and AI‑powered channels
- Designing future‑ready service models, enabled by platforms, data and automation
- Embedding GenAI, intelligent automation and decisioning into customer service journeys and operations
- Supporting clients to define a customer‑first mindset, helping them shape their business and operating models
- Ensuring the services we design deliver real value for customers
We work across the full lifecycle: from ambition and vision, through design and experimentation, to scaled delivery and adoption.
What you’ll do
- Lead in the Song Service practice
- Define how Song builds, ships and sustains AI systems at enterprise scale
- Own the technical delivery standard across multiple agentic programmes; architecture governance, eval frameworks, compliance posture and engineering excellence
- Drive thought leadership on production AI engineering, multi‑agent systems and the future of agentic delivery
- Drive Song Services’ point of view on AI engineering, agentic infrastructure and production AI
- Build and own strategic partnerships with platform providers: Anthropic, Open AI, AWS, Google, Microsoft and upcoming vendors.
- Represent Song at industry events, analyst briefings and executive client forums as a technical authority
- Drive commercial growth
- Own C‑suite and technical executive relationships across Song’s largest agentic clients
- Lead pursuit activity on major engineering programmes; shaping proposals, pricing and commercial structures
- Identify and convert new commercial opportunities within existing and new accounts
- Build Song’s pipeline of agentic delivery engagements across Telco, Financial Services, Public Sector and Resources
- Build the team and the talent
- Recruit, develop and retain the best AI engineering talent in the market
- Build a culture of craft, learning and technical excellence across the practice
- Sponsor senior engineering talent and build the next generation of AI delivery directors
- Partner with Accenture’s global AI and technology practices to bring the best of the firm to Song clients
Experience Required
- Extensive hands‑on engineering experience with a proven track record of leading enterprise‑scale AI delivery, owning technical practices and driving commercial outcomes in professional services.
- Deep engineering background with production experience in Python and similar languages across AI systems
- Proven track record of architecting and leading delivery of RAG pipelines, multi‑agent systems and LLM‑based products at enterprise scale across multiple clients
- Deep hands‑on experience across at least major cloud AI platforms (AWS Bedrock, GCP Vertex AI, Azure AI Studio)
- Experience designing and owning eval frameworks, red‑teaming processes and AI compliance postures
- Proven track record of leading and developing engineering teams in agile, client‑facing delivery contexts
- Demonstrable commercial impact; pipeline generation, major account wins or significant scope expansion on existing accounts
AI, data and technology awareness
A working awareness of the technology landscape that underpins agentic delivery — enough to engage credibly with engineering teams and clients, and to shape and govern solutions. This includes familiarity with:
- Agentic frameworks (e.g. LangGraph, LangChain, CrewAI, AutoGen, Agentforce)
- Foundation model providers (e.g. Claude, OpenAI, Gemini, AWS Bedrock)
- Retrieval and data approaches such as vector databases (e.g. Pinecone, Weaviate, LlamaIndex, pgvector)
- Cloud AI platforms (AWS, GCP and Azure)
- How AI solutions are tested, deployed and maintained reliably in production
- The AI governance and regulatory landscape, including the EU AI Act, bias and model drift, and what it means for responsible delivery
