AI Engineer
Core
Design, build, and deploy agentic AI systems, orchestration workflows, and intelligent automation pipelines for public sector and enterprise clients.
Role type
Senior AI Engineer (Agentic AI & MLOps)
Builds
Autonomous AI agents, RAG systems, agent-to-agent communication protocols, and scalable inference infrastructure.
Domain
Artificial Intelligence, Automation, Cloud Infrastructure, Enterprise Software
Deliverable
production ML models | product features | infrastructure
Required skills
Agentic AI design, LLM orchestration (LangChain, LangGraph), RAG implementation, MRP (Memory, Reasoning, Planning), Cloud deployment (AWS/Azure/GCP), Containerization (Docker), Kubernetes, CI/CD (Argo), Python, Model training/fine-tuning (TensorFlow/PyTorch)
Preferred skills
Agent-to-Agent (A2A) protocol design, MLOps tooling, Knowledge graphs, Semantic web technologies, Prompt engineering
Technologies
LangChain, LangGraph, Microsoft Bot Framework, Ollama, vLLM, TensorFlow, PyTorch, Docker, Kubernetes, Argo Workflows, Argo CD, AWS, Azure, GCP
Responsibilities
Design and build sophisticated AI agents with independent operation and self-correction; Develop orchestration workflows for conversational and task-oriented agents; Implement RAG systems connecting agents to live knowledge bases; Deploy and manage AI systems on major cloud platforms ensuring high availability; Containerise applications and orchestrate deployments with Kubernetes; Train, fine-tune, and optimise custom AI models using TensorFlow or PyTorch.
Seniority
Senior, hands-on IC
