AI CX Delivery Consultant

Overview

In this role, you design and deploy agentic AI experiences that bridge CX design and engineering for production readiness. You’ll work within Accenture Song’s Service practice to deliver measurable outcomes by embedding GenAI, automation, and AI-driven CX into client journeys. You’ll collaborate with designers and strategy leads to translate CX needs into production AI solutions, tackling complex, scalable use cases. This is a growth-oriented, hands-on engineering role in a fast-moving, client-centric environment.

Pay / Benefits

• competitive salary
• annual performance bonus
• potential equity
• health and wellbeing benefits
• 30 days of leave plus 3 volunteering days
• family-friendly and flexible policies

Responsibilities

• Design and deploy end-to-end agentic experiences in production
• Prompt engineer, test, and iterate AI agents across client use cases
• Work with LangGraph, LangChain, Claude, Code/Codex/Gemini and RAG pipelines
• Implement RAG and vector database solutions (Pinecone, Weaviate, LlamaIndex)
• Deploy AI solutions on AWS Bedrock, GCP Vertex AI or Azure AI Studio
• Bridge CX design with engineering to ship final agents
• Collaborate with AI Experience Designers, Conversational PMs and Strategy leads
• Contribute to reusable agentic delivery assets and accelerators
• Stay current with agentic tooling, model releases, and platform updates
• Develop production AI engineering capabilities within a high-growth environment

Key requirements

• Professional engineering experience with hands-on involvement in AI or agentic systems in production
• Strong programming background in Python and similar languages
• Hands-on experience with at least one agentic framework (LangGraph, LangChain, CrewAI or equivalent)
• Experience with foundation model APIs (Claude API, OpenAI API or Vertex AI)
• RAG implementation experience with at least one vector database
• Cloud deployment experience across AWS, GCP or Azure
• Evidence of AI systems built and deployed to production

• Clear communication and ability to explain technical decisions to non-engineers
• Collaborative and team-oriented in cross-disciplinary delivery environments
• Self-directed, proactive delivery management
• Agentic frameworks: LangGraph, LangChain, CrewAI, Agentforce or similar
• Foundation model providers: Claude, OpenAI, Gemini, AWS Bedrock
• Vector databases: Pinecone, Weaviate, LlamaIndex, pgvector

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