AI Delivery Tech Lead

Accenture Song is the world’s largest tech‑powered creative group. The AI Delivery Tech Lead will be accountable for Song’s most complex agentic programmes, shaping and delivering transformational customer platform solutions and driving commercial growth.

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