Senior Agentic AI & Data Engineer

What you will do

In the GenAI world, three years is a lifetime. At Accenture, we focus on autonomous Multi‑Agent Systems. If juggling models, building robust RAG systems, and deploying via MCP is second nature to you, we consider you ready to take ownership of senior‑level engineering challenges in secure, data‑driven AI environments.

You will:

• Model Optimization: Orchestrate agents using the most suitable models for each use case (OpenAI, Claude 3.5, Gemini) and deploy open‑source models from Hugging Face. Build agent systems using platforms such as Google Antigravity.
• Advanced Data Architecture: Design pipelines for embeddings, hybrid search, and re‑ranking to support large‑scale Conversational Analytics.
• MCP Integration: Build secure Model Context Protocol servers bridging AI systems with enterprise databases.
• Cloud & AI Governance: Deploy agentic solutions into production environments (AWS, Azure, GCP) ensuring strict adherence to Responsible AI guardrails.
• Work daily with: Python, Multi‑Agent Systems, MCP, Vector DBs (Pinecone/Milvus), LLMs (Commercial & Open Source), RAG, MLOps, AWS/Azure/GCP.

🎯 Interview Note (Vibe Coding):

Have your development environment ready (Windsurf, Cursor, Antigravity). During the technical call, we will co‑build or debug a specific agentic flow to understand your engineering approach.

Flexible: The work location for this role may include a mix of working remotely (most of the time), onsite at a client or in an Accenture office – depending on specific project circumstances. With all our roles, there is some in‑person time for collaboration, learning and building relationships with clients, peers, leaders, and communities. As an employer, we will be as flexible as possible to support your specific work/life needs.

What we offer

• A permanent employment contract
• Individual support of a People Lead and a clearly defined path of professional development, including the possibility of a session with a Coach
• A comprehensive training package, including:
• soft skills, technical and language training
• access to e‑learning platforms
• Gallup test
• GenAI training
• possibility of co‑financing courses and certifications
• Employee Assistance Program offering legal, financial and psychological consultations
• Employee Share Purchase Plan — employees who own company shares are automatically eligible for quarterly dividends
• Paid employee referral program
• Private medical care and life insurance
• Access to the Worksmile benefits platform (including the Multisport card)

Requirements

• Minimum 2–3 years of commercial experience in AI / Data Engineering / Software Engineering.
• Deep understanding of Agentic Architectures (LLM as an engine vs. an Agent with memory and tools).
• Hands‑on experience with Vector DBs, chunking strategies, and optimization of vector queries.
• Proficiency in MCP implementation and ADK (Agent Development Kit) frameworks.
• Cloud experience (AWS / Azure / GCP) and fluent English (B2+/C1).

BONUS POINTS IF YOU HAVE

• Experience building multi‑agent systems using orchestration frameworks or Agent‑First platforms.
• Proven ability to optimize RAG architectures for large‑scale analytics.
• Hands‑on experience with MLOps and secure deployment patterns in enterprise settings.

Research indicates that some candidates, especially the most diverse ones, may hesitate to apply for positions if they don't meet all requirements. If you believe you possess the necessary skills, even if not meeting every requirement, we wholeheartedly encourage you to submit your application.