Builds agentic LLM systems, RAG, and prompt engineering — directly related to AI-first dev workflows and tooling.
About the Role
As a Forward Deployed Lead Engineer at Accenture you will lead the architecture, design, and delivery of enterprise-scale AI solutions, integrating LLMs, agentic AI, RAG, and workflow orchestration across enterprise systems. The role focuses on deploying AI workflows, defining scalable integrations, and providing technical leadership while engaging with business stakeholders. Requires strong Python expertise, generative AI experience, a minimum of 7.5 years' professional experience, and 15 years of full-time education.
Job Description
Role
Lead the architecture, design, and delivery of enterprise-scale AI solutions for complex business environments. Provide technical leadership across initiatives involving LLMs, agentic AI, RAG, workflow orchestration, and enterprise integrations.
Key Responsibilities
- Lead architecture and implementation of enterprise AI solutions.
- Analyze complex business challenges and define scalable AI solution architectures.
- Lead solutioning workshops and architecture discussions with business and technical stakeholders.
- Define architectures for AI agents, RAG systems, vector search, and intelligent workflow orchestration.
- Drive technical decisions on model selection, prompt engineering, evaluation frameworks, governance, and responsible AI.
- Design enterprise integration patterns across business applications and cloud platforms.
- Mentor engineers, conduct design reviews, and establish engineering best practices.
- Collaborate with stakeholders, architects, and engineering teams to deliver business outcomes.
Requirements
- Minimum 7.5 years of professional experience.
- Strong expertise in Python and enterprise application development.
- Experience designing and delivering AI-powered solutions leveraging LLMs.
- Deep understanding of agentic AI, workflow orchestration, and enterprise automation.
- Experience with RAG architectures, vector databases, embeddings, and semantic search.
- Experience with prompt engineering, model evaluation, and AI governance.
- Strong solution architecture, system design, problem-solving, consulting, and stakeholder management skills.
- 15 years of full-time education required.
Preferred Skills
- Experience with Google Cloud Platform (GCP), Gemini, Vertex AI, Agent Builder, or Vertex AI Search.
- Familiarity with frameworks such as LangChain, LangGraph, LlamaIndex, CrewAI, ADK, or equivalents.
- Experience with open-source models and enterprise AI platforms.
- Experience designing cloud-native and scalable enterprise architectures.
Qualifications
- Educational qualification: 15 years full-time education.
- Professional experience: minimum 7.5 years, with demonstrated experience leading design and delivery of enterprise AI or automation solutions.