Are you passionate about Artificial Intelligence, Generative AI, and building intelligent systems that solve real business problems?

We're looking for a Senior Data Scientist who thrives on designing enterprise-scale AI solutions, building autonomous AI agents, and creating intelligent platforms that deliver meaningful impact. This is an opportunity to work on cutting-edge AI technologies with a global team while helping shape the future of enterprise AI.

As a Senior Data Scientist, you'll play a key role in designing, building, and supporting enterprise AI platforms. Your responsibilities will include:

• Designing and building agentic AI system architectures using Amazon Bedrock AgentCore and modern agent frameworks
  
• Creating intelligent multi-step reasoning workflows with tool integration and orchestration
  
• Defining AI model strategies, including architecture selection, fine-tuning, inference, and performance optimisation
  
• Designing scalable and resilient AI deployments using Docker and Kubernetes
  
• Building secure, low-latency networking architectures for AI workloads
  
• Conducting systems performance engineering, including hardware selection, load testing, stress testing, and capacity planning
  
• Establishing MLOps and GenAI Ops practices, including CI/CD pipelines, model versioning, and deployment automation
  
• Implementing monitoring, logging, observability, and incident response for production AI environments
  
• Building enterprise Retrieval-Augmented Generation (RAG) solutions and intelligent AI workflows
  
• Providing technical leadership, mentoring engineers, and influencing architecture and engineering best practices
  

Requirements

Essential Skills

• Amazon Bedrock AgentCore
  
• Agent frameworks such as LangChain, LangGraph, or Strands Agents
  
• Designing agentic AI architectures
  
• Multi-agent orchestration and workflow automation
  
• PyTorch
  
• TensorFlow
  
• Python
  
• Docker
  
• Kubernetes
  
• Production API development
  
• Retrieval-Augmented Generation (RAG)
  
• MLOps and GenAI Ops
  
• CI/CD for Machine Learning
  
• Model versioning and deployment automation
  
• AI observability and monitoring
  
• Networking for machine learning workloads
  
• Systems performance engineering
  

Advantageous Skills

• Amazon Bedrock
  
• Terraform or Terragrunt
  
• AWS Lambda
  
• Step Functions
  
• EventBridge
  
• Cloud security and IAM best practices
  
• Data Engineering and ETL pipelines
  
• Feature Stores
  
• Prometheus
  
• Grafana
  
• CloudWatch
  
• Hybrid or multi-cloud AI deployments
  
• Model optimisation techniques such as batching, quantisation, and distillation
  
• Enterprise environments operating within regulated industries
  

Qualifications and Experience

• A degree in Computer Science, Engineering, Statistics, or a related field
  
• A proven track record of delivering enterprise-scale AI solutions
  
• Experience owning AI architecture from design through to production
  
• Strong stakeholder management and technical leadership experience
  

Benefits

• Cutting edge global IT system landscape and processes
  
• Flexible working of 1960 hours in a 12-month period
  
• High Work-Life balance
  
• Remote / On-site work location flexibility
  
• Highly motivating, energetic, and fast-paced working environment
  
• Modern, state-of-the-art offices
  
• Dynamic Global Team collaboration
  
• Application of the Agile Working Model Methodology