Senior Data Scientist (AI & Agentic Systems)

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