AI Delivery Tech Lead (CL8)

Overview

In this AI Delivery Tech Lead role, you will architect and deliver enterprise-scale AI-driven customer experiences, moving agentic products from prototype to production. You’ll work within the Service practice to shape measurable outcomes by embedding GenAI, automation, and data-driven design into customer service journeys. You collaborate with cross-functional teams to deliver scalable, observable, compliant platforms and to guide clients through architecture and delivery decisions. This role offers hands-on impact, leadership development, and exposure to a global network of AI and engineering experts.

Pay / Benefits

• competitive salary
• annual performance bonus
• equity opportunities
• 30 days annual leave + 3 volunteering days
• family-friendly policies
• flexible work policies

Responsibilities

• Architect and build agentic experiences for production.
• Hands-on CCaaS/AI design and build to scale customer experience platforms.
• Drive CCaaS and AI innovation for connected, always-on service models.
• Transform journeys using data, CCaaS, and AI to create seamless experiences.
• Contribute to RAG pipelines, multi-agent orchestration, and evaluation frameworks.
• Advise on AI architecture decisions, platform selection, and build-vs-buy trade-offs.
• Define technical delivery approaches and infrastructure strategies.
• Engage with client technical teams at Manager/Lead level and translate constraints into recommendations.
• Deliver transformational customer platform solutions and contribute to multi-system programs.
• Contribute to technical standards, quality frameworks, and governance; ensure scalability, observability, and compliance.
• Collaborate with Forward Deployed Engineers, Experience Designers, and Strategy leads.
• Grow the practice by mentoring juniors and contributing to sales, propositions, and thought leadership.

Key requirements

• Strong engineering background with production experience in Python (and related AI languages).
• Experience building or contributing to RAG pipelines, multi-agent systems, or LLM-based products at 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 AI quality metrics.
• Portfolio of deployed or near-production AI systems, in regulated/enterprise environments.
• Experience in agile, client-facing delivery within engineering teams.
• Practical AI/tech awareness: LangGraph, LangChain, CrewAI, Agentforce or similar; foundation models (Claude, OpenAI, Gemini, AWS Bedrock); vector stores (Pinecone, Weaviate, LlamaIndex, pgvector); CI/CD for AI; EU AI Act compliance and bias/model drift considerations.
• Comfortable discussing architecture decisions and delivery trade-offs with client stakeholders; familiarity with Telco or Financial Services is a plus.

• Clear communication of complex technical topics to clients
• Leadership potential or experience in team settings
• Ability to articulate architecture trade-offs under delivery pressure
• Python and AI-focused languages
• RAG pipelines and multi-agent systems
• LLM-based product development

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