Artificial Intelligence Engineer – Agentic AI Specialist

About the role

The Agentic AI Engineer designs, builds, and deploys autonomous AI agents that enhance research and corporate workflows. Working closely with the AI Platform Engineer, you will translate organisational needs into production‑ready solutions while respecting data protection, safety, and governance standards.

Key responsibilities

• Design and implement autonomous agents capable of reasoning, planning, and goal‑driven execution with minimal human input.
• Develop multi‑step workflows that combine large language model (LLM) reasoning, tool usage, and structured decision‑making.
• Build and maintain prompt‑engineering strategies, including chain‑of‑thought and role‑based prompting.
• Create memory architectures for short‑term and long‑term context awareness.
• Construct retrieval‑augmented generation (RAG) pipelines linking agents to internal knowledge bases and document repositories.
• Integrate agents with internal APIs, data sources, and enterprise systems, optimizing vector search and embedding models.
• Design multi‑agent orchestration patterns, routing logic, and inter‑agent communication protocols.
• Leverage managed services such as AWS Bedrock AgentCore and Microsoft Foundry Agent Service, evaluating and recommending platform capabilities.
• Implement safety guardrails, human‑in‑the‑loop approvals, and observability pipelines for monitoring agent decisions.

Required profile

• Strong background in artificial intelligence, machine learning, or related fields.
• Proven experience building autonomous or agentic AI systems.
• Ability to work collaboratively with platform engineers and cross‑functional teams.
• Understanding of data protection, safety, and governance requirements for AI deployments.

Required skills

• Large Language Models (LLM) development and integration
• Retrieval‑Augmented Generation (RAG) pipelines
• Prompt engineering (chain‑of‑thought, role‑based)
• Memory architectures for context‑aware agents
• Vector search, embedding models, and vector databases
• API integration and enterprise system connectivity
• Experience with managed services such as AWS Bedrock AgentCore and Microsoft Foundry Agent Service
• Cloud platform knowledge for deploying AI solutions