Enterprise Consultant – Technology Architecture Team Lead/Consultant | Mid-Level | Full time

Job title: Enterprise Consultant – Technology Architecture Team Lead/Consultant | Mid-Level | Full time

About the Role Accenture's AI Native Transformation team is seeking an Enterprise Consultant/Technology Architecture Team Lead to help clients design and deliver AI-native transformations at scale. This mid-level, full-time role combines hands-on software engineering, enterprise architecture, and leadership to build multi-agent, event-driven architectures that blend AI with traditional distributed systems. You will work across industries to reimagine core processes and establish scalable, secure cloud environments.

What You'll Do

• Design and implement agentic architectures and multi-agent orchestration patterns to build AI-native, scalable enterprise solutions.
• Collaborate with clients in financial services, healthcare, procurement, retail, and logistics to define strategy and deliver tangible business value.
• Use AI agents to map dependencies, analyze Git history, discover hidden coupling, and identify knowledge concentration to guide transformations.
• Build composable, event-driven systems with real-time feedback loops and human-AI collaboration at scale, wrapping legacy cores as needed.
• Work in a deeply hands-on, battle-hardened team of AI transformation thought leaders; lead-from-the-front style expected.
• Travel may be required for projects; amount varies from 0 to 100% depending on business need and client requirements.

What We're Looking For

• Minimum of 2 years of hands-on experience building interesting and innovative applications, or equivalent open-source contributions.
• Minimum of 2 years of experience explaining complex AI concepts to non-technical audiences.
• Minimum of 2 years of experience designing software systems that incorporate AI components, with understanding of when AI is appropriate, limitations, and fallback mechanisms.
• Minimum of 4 years of experience working in an agile team.
• Minimum of 2 years of experience and understanding of AI system observability and debugging (LLM tracing, analyzing failure modes).
• Bachelor's degree or equivalent (minimum 12 years) work experience. If Associate’s Degree, must have minimum 6 years work experience.
• Bonus points: experience building with LLM APIs (Claude, GPT-4, etc.); designing multi-agent systems with distinct roles; MCP Server/Client patterns; agentic frameworks (LangChain, LlamaIndex); analysis of legacy architectures; hands-on with vector databases and RAG architectures (Qdrant, Pinecone, ChromaDB, Weaviate); graph databases/knowledge graphs (Neo4j, Neptune); cloud platforms (AWS, Azure, GCP); event-driven architectures and streaming tech (Kafka, Kinesis, EventBridge).

Nice to Have

• Experience designing multi-agent systems with distinct roles; MCP Server and Client including standard connection, tools and data exposure as well as specific tools.
• Experience analyzing and transforming existing systems—brownfield work; systematic dependency analysis, git history mining, and architectural discovery.
• Hands-on experience with agentic frameworks (LangChain, LlamaIndex).
• Hands-on experience with vector databases and RAG architectures (Qdrant, Pinecone, ChromaDB, Weaviate).
• Understanding of graph databases and knowledge graphs (Neo4j, Neptune) for semantic relationships and ontology modeling.
• Hands-on experience with cloud platforms (AWS, Azure, or GCP).
• Experience with event-driven architectures and streaming technologies (Kafka, Kinesis, EventBridge).

Compensation & Benefits

• Salary not disclosed.
• Travel opportunities may be required depending on client needs.