We are seeking a passionate and technically strong Agentic AI Engineer to join our Regulatory Technology & Data (RTD) offering.
This role focuses on designing, building, and operationalising agent-based AI systems that support regulatory, risk, and data-intensive use cases - augmenting human decision-making while meeting enterprise-grade standards for safety, governance, and reliability.
You will work at the intersection of Generative AI, autonomous agents, cloud platforms, and regulated environments, contributing to production-grade systems rather than research prototypes.
Key Responsibilities
Agentic System Design & Engineering:
- Design and implement agent-based architectures, defining how agents:
- Gather and reason over context
- Plan and make decisions
- Coordinate with other agents
- Interact safely with tools, APIs, and enterprise systems
- Build and maintain robust agent runtime environments that support cognition, orchestration, and execution at scale.
- Implement reasoning and control frameworks (e.g. planning, reflection loops, evaluation pipelines) to enable safe, traceable, and reliable agent behaviour.
Platforms, Frameworks & Protocols
- Develop using modern Agentic AI frameworks and orchestration tools, such as:
- LangGraph
- Langflow
- N8N
- LangChain
- Apply knowledge of agent communication and orchestration protocols (e.g. MCP, ACP, A2A, ANP) where appropriate.
Security, Governance & Observability
- Design and implement security, observability, and governance controls aligned to regulated or high鈥憆isk environments.
- Establish guardrails to ensure alignment, safety, and reliability for semi鈥慳utonomous or autonomous operations.
- Monitor, evaluate, debug, and continuously improve agent performance using telemetry, evaluation signals, and feedback loops.
Human-AI Collaboration
- Design human鈥慽n鈥憈he鈥憀oop and human鈥憃n鈥憈he鈥憀oop workflows that ensure AI augments business capability, whilst minimising operational or regulatory risk.
- Optimise user interactions and hand鈥憃ffs between operational teams and agentic systems.
Technical Requirements
Core Skills:
- Strong programming capability with Python (required).
- Experience building, testing, and deploying LLM鈥慴ased or agentic systems in real-world environments.
- Solid understanding of software architecture, APIs, and distributed systems.
Platforms & Engineering Stack (Strongly Preferred):
- Experience with some or all of the following:
- Python, ASP.NET Core, Entity Framework
- Angular or React
- PostgreSQL or similar relational databases
- MongoDB or similar document databases
- Git
- Experience with virtualisation and containerisation platforms, e.g Docker, Kubernetes.
Cloud & AI (Advantageous):
- Azure AI Foundry / Amazon Bedrock Experience
- General cloud experience with AWS, Azure and/or GCP.
- Cloud architecture and/or AI-related certifications are advantageous.