AI & Agentic Technical Delivery Lead (Customer)

Overview

In this role you lead GenAI and agentic delivery across client engagements, shaping production-ready architectures and governance. You review architectures, set quality standards, and steer complex delivery to meet business outcomes. You work with cross-functional teams to translate client ambitions into concrete technical plans and realistic timelines. This is a senior, client-facing leadership role that blends advisory, delivery, and practice development to advance Accenture Song’s AI capabilities.

Pay / Benefits

• 30 days of leave
• 3 volunteering days
• Family-friendly policies
• Flexible work policies
• Pension plan
• Private healthcare insurance plan and Mental Wellbeing support

Responsibilities

• Serve as the senior technical authority on GenAI and agentic delivery across client engagements
• Review end-to-end solution architectures including LLM selection, RAG pipelines, and guardrails
• Define standards separating POC from deployable product and address blurred boundaries
• Identify and mitigate technical risks early (data quality, latency, hallucinations, integration)
• Act as a technical quality layer across engagements by validating outputs and solutions
• Advise senior client stakeholders on feasibility and the path to production
• Shape and size AI solutions with concrete requirements and delivery estimates
• Lead and support cross-functional delivery teams (on-shore, near-shore, off-shore)
• Unblock delivery by diagnosing root causes and accelerating progress
• Establish scalable engineering practices (code review, testing, deployment patterns)
• Provide delivery realism in planning (timelines, resources, scope)
• Develop GenAI delivery capability through knowledge sharing and coaching
• Be a credible external voice on GenAI delivery in client interactions and pitches
• Build reusable delivery assets, architectures, and evaluation frameworks
• Stay current on GenAI landscape and sensors of capability gaps
• Contribute to growth of Accenture Song’s AI capability

Key requirements

• Proven GenAI delivery with production systems (RAG pipelines, agentic workflows, multimodal apps)
• Hands-on expertise across GenAI delivery stack (LLM APIs, vector DBs, embedding models, orchestration frameworks, deployment)
• Lifecycle experience from POC to production, including evaluation design, prompt engineering at scale, guardrails, cost, latency, monitoring
• Ability to identify breaking points and optimize architecture for cost and performance
• Familiarity with agentic AI patterns and real delivery contexts

• Executive communication
• Strategic thinking
• Constructive challenging of assumptions
• LLM APIs (OpenAI, Anthropic, Google, open-source)
• Vector databases
• Embedding models

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