At a Glance
- Tasks: Lead the delivery of AI systems and transform customer experiences at scale.
- Company: Join Accenture Song, a global leader in tech-powered creativity.
- Benefits: Enjoy competitive salary, flexible work, and generous leave policies.
- Other info: Collaborative environment with excellent growth opportunities and a focus on well-being.
- Why this job: Be at the forefront of AI innovation and make a real impact.
- Qualifications: Hands-on experience in AI systems and strong engineering skills required.
The predicted salary is between 63000 - 77000 £ 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 play a key role in delivering AI systems at enterprise scale; contributing to and supporting the delivery of transformational customer platform solutions that take agentic products from prototype to production.
Our mission is to help our clients to deliver exceptional human and agentic experiences that deliver simplicity, cost transformation, and an engine for growth. Every interaction is a moment to resolve, deepen trust, build loyalty, and demonstrate the brand promise when it counts most.
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.
As a team, the Service practice sits within Accenture Song. Our vision is to deliver iconic client outcomes. A shared purpose for our people; to grow, to build new skills, and do our best work.
We focus on:
- Reinventing customer service across physical, digital/app-based and AI-powered channels
- Data-driven transformation across service to reduce cost and drive growth
- 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
- Delivering measurable business outcomes, not just great experiences
We work across the full lifecycle: from ambition and vision, through design and experimentation, to scaled delivery and adoption.
What you'll do:
- Architect and build agentic experiences to production
- Work in a technical capacity contributing through hands-on CCaaS/AI design and build to deliver customer experience and contact platforms at scale
- Be at the forefront of CCaaS and AI innovation, helping clients build connected, always-on service models for their customers
- Transform customer journeys and service interactions using data, CCaaS platforms and AI to create seamless and consistent experiences
- Contribute to building and delivery of RAG pipelines, multi-agent orchestration and eval frameworks for enterprise-scale AI deployments
- Support client teams on AI architecture decisions, platform selection and build vs buy trade-offs
- Define technical delivery approaches and infrastructure strategies
- Engage credibly with client technical teams at Manager/Lead level
- Translate complex technical constraints into clear strategic recommendations
- Contribute to delivering transformational customer platform solutions for clients who want deeper understanding of how customers engage with their products and services
- Contribute to engineering teams across complex, multi-system agentic programmes
- Contribute to technical standards, quality frameworks and architecture governance
- Ensure systems are designed for scalability, observability and compliance
- Collaborate closely with Forward Deployed Engineers, Experience Designers and Strategy leads
- Support more junior engineers and develop technical capability within the practice
- Contribute to sales, propositions and go-to-market activity
- Contribute to thought leadership on production AI engineering and agentic delivery
Experience Required:
- Solid hands-on engineering experience with a track record of building AI systems, ideally with some exposure to enterprise or production environments.
- Strong engineering background with production experience in Python and similar languages across AI systems
- Experience building or contributing to RAG pipelines, multi-agent systems or LLM-based products, ideally at meaningful scale
- Hands-on experience with at least one major cloud AI platform (AWS Bedrock, GCP Vertex AI or Azure AI Studio)
- Experience designing eval frameworks, red-teaming processes and quality measurement for AI systems
- A portfolio or track record that demonstrates deployed or near-production AI systems, with an interest in regulated or enterprise environments
- Some experience working within engineering teams in agile, client-facing delivery contexts
AI, data and technology awareness:
- Practical experience with agentic frameworks: LangGraph, LangChain, CrewAI, Agentforce or similar
- Foundation model providers: Claude Code/Codex/Gemini, OpenAI or AWS Bedrock
- Vector databases: Pinecone, Weaviate, LlamaIndex or pgvector
- Cloud platforms: AWS Bedrock, GCP Vertex AI or Azure AI Studio
- CI/CD for AI: version-controlled prompts, automated testing, deployment pipelines
- EU AI Act compliance, bias auditing and model drift detection
Leadership & consulting skills:
- Some technical leadership experience or a demonstrable appetite to grow into team leadership
- Clear communication of complex technical topics to client stakeholders
- Experience making and communicating architecture trade-offs under delivery pressure
- Awareness of commercial models and technical delivery in professional services
- Comfortable leading within agile, collaborative, fast-moving consulting environments
- Experience in Telco or Financial Services
Set yourself apart:
- Certifications in AWS, GCP, Azure or Anthropic AI platforms
- Open-source contributions to agentic or LLM tooling
- Contact centre platform experience (e.g. Genesys, Sierra, Decagon, Parloa, PolyAI, NICE Cognigy, Agentforce Contact Centre and Amazon Connect)
- EU AI Act or AI governance certifications or published guidance
- Experience in Telco, Financial Services or Public Sector; our highest-demand client verticals
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.
- 25 days of leave to spend each year plus 3 extra volunteering days per year for charitable work of 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.
Flexibility and mobility are required to deliver this role as there will be requirements to spend time onsite with our clients and partners to enable delivery of the outstanding services we are known for.
Please note that with all our roles, you should expect some in-person time for collaboration, learning and building rapport with clients, peers, leaders and communities. As an employer, we will be as flexible as possible to support your specific work/life needs.
Accenture is an equal opportunities employer and encourages applications from all sections of society and does not discriminate on grounds of race, religion, belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation or gender identity.
AI Delivery Tech Lead (CL8) in London employer: WeAreTechWomen
At Accenture, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration. Our London office provides unparalleled opportunities for professional growth, with access to cutting-edge AI technologies and the chance to work alongside industry leaders. We are committed to your development, ensuring you have the resources and support needed to thrive in your role as a Senior Manager/Associate Director in AI architecture.
StudySmarter Expert Advice🤫
We think this is how you could land AI Delivery Tech Lead (CL8) in London
✨Join Local Tech Meetups
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We think you need these skills to ace AI Delivery Tech Lead (CL8) in London
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at WeAreTechWomen.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at WeAreTechWomen and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at WeAreTechWomen
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If WeAreTechWomen uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.
