Senior AI Engineer
The Source
Bracknell, United Kingdom
2 days ago
Role details
Contract type
Permanent contract Employment type
Full-time (> 32 hours) Working hours
Regular working hours Languages
English Experience level
Senior Compensation
£ 110KJob location
Remote
Bracknell, United Kingdom
Tech stack
Artificial Intelligence
Amazon Web Services (AWS)
Continuous Integration
Distributed Systems
Identity and Access Management
Microsoft Office
Open Source Technology
Generative AI
Kubernetes
Machine Learning Operations
Terraform
Docker
Databricks
Job description
Staff AI Engineer Location: Remote Salary: 100-110k/annum (DOE) Industry: Life Sciences
Role Overview We are seeking a Staff AI Engineer to design, build, and scale production-grade ML, Generative AI, and Agentic AI systems within our business domain.
Embedded within the Enterprise Data Office, you will be the senior hands-on technical leader translating complex business problems into secure, scalable, and cost-efficient AI solutions on AWS and Databricks.
This is a deeply technical role focused on engineering excellence, operational resilience, and measurable business impact.
Key Responsibilities
- Architect and implement end-to-end AI systems (RAG, vector search, Real Time and asynchronous inference).
- Productionize multi-agent workflows and Foundation Model integrations.
- Lead MLOps, LLMOps, and AgentOps practices (CI/CD, evaluation, monitoring, drift detection).
- Build secure, GPU-optimized, cloud-native AI platforms using Terraform, Docker, and Kubernetes.
- Ensure AI security by design (private endpoints, PII redaction, least-privilege IAM).
- Optimize cost-performance trade-offs across proprietary and open-source models.
- Lead technical design reviews and mentor engineers in AI-native development practices.
Experience
- Expert building AI Architectures in AWS on Databricks.
- Strong experience with RAG, large-scale inference, and distributed systems.
- Hands-on MLOps/LLMOps in production environments.
- 5+ years experience building scalable, secure AI services in enterprise settings.
- Strong communicator able to articulate engineering trade-offs clearly.
- Databricks Certified (preferred), AWS Certified (preferred)
Requirements
- Expert building AI Architectures in AWS on Databricks.
- Strong experience with RAG, large-scale inference, and distributed systems.
- Hands-on MLOps/LLMOps in production environments.
- 5+ years experience building scalable, secure AI services in enterprise settings.
- Strong communicator able to articulate engineering trade-offs clearly.
- Databricks Certified (preferred), AWS Certified (preferred)
