About the position
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.
If you're someone who enjoys solving complex technical challenges, leading architectural decisions, and turning innovative ideas into production-ready solutions, this could be the perfect role for you.
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
RequirementsEssential 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
Desired Skills:
- amazon bedrock
- LangChain
- LandGraph
- AI Architectures
- Python
- Agentic system architectures
Desired Qualification Level:
About The Employer:
