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About the Role
The AI DevOps Engineer is a highly technical, hands-on role responsible for the end-to-end delivery and operations of DevOps environments. This role is key to an ambitious technology modernization journey focused on increased adoption of AI, microservices, and public cloud, evolving a global hybrid architecture across multiple data centers, on-premise, Azure, and AWS.
Responsibilities
- End-to-end delivery and operations of DevOps environments.
- Automating and standardizing to ensure consistency, scalability, and reliability across all environments.
- Integrating AI tools, such as embedding LLMs APIs or agents in pipelines.
- Orchestrating GPU workloads.
- Building or using agents for AI Automation.
- Integrating DevOps infrastructure with MCPs.
Requirements
- Very good understanding of AI infrastructure and DevOps.
- Experience with RAG pipelines, MLOps frameworks (Kubeflow, MLflow, Argo, Airflow), data pipelines, and versioning.
- Experience with predictive operations tools (prophet, Dynatrace etc).
- Very strong, AI-focused, Azure and AWS expertise.
- Experience with Azure Foundry and Bedrock.
- Experience with Terragrunt and Terraform.
- Experience with Python.
- Very good understanding of containerization technologies.
- Experience building or using agents.
- Experience integrating DevOps infrastructure with MCPs.
- Extensive experience working both independently and as part of a diverse team.
- Excellent organizational skills, open communication, and a collaborative approach.
- Commitment to continuous improvement, learning from others, and sharing knowledge.
Skills
- AI infrastructure
- DevOps
- RAG pipelines
- MLOps frameworks
- Kubeflow
- MLflow
- Argo
- Airflow
- Data pipelines
- Data versioning
- Predictive operations tools
- Prophet
- Dynatrace
- AI tools integration
- LLMs APIs
- Agents
- Azure
- AWS
- GPU workload orchestration
- Azure Foundry
- Azure Bedrock
- Terragrunt
- Terraform
- Python
- Containerization technologies
- Infrastructure testing frameworks
- Terratest
- Terraform Test
- Molecule
- JUnit
- pytest
- Kubernetes engineering
- Linux administration
- Windows administration
- Network automation
- Java troubleshooting
- C# troubleshooting
- CI/CD
- GitHub Actions
- TeamCity
- Artifact repository management
- Nexus
- Artifactory
- Observability
- Monitoring
- Tracing
- OpenTelemetry
- Prometheus
- ELK
- Tempo
- Jaeger
- Platform engineering
- Data platform experience
- Kafka
- Redis
- Chaos engineering
- Resilience testing
- Gremlin
- LitmusChaos
Location
- Global
Work Type
- Hybrid
- Full-time
Experience Level
- Individual contributor
- Extensive experience
About the Company
- Our Technology Infrastructure team operates globally and is responsible for every aspect of the firm's hybrid platform, from EUC/Office environments to Trading and Core service Co-Location Data Centres, and extends to Public Cloud.
- We deliver top-tier technology services to a dynamic and demanding Trading organisation.
- We continuously evolve and transform our platforms to maintain a competitive edge.
- We innovate to provide valuable solutions and leverage our skilled Technology teams to deliver against rapidly changing business requirements.
- Over the past four years, we've modernized our core trading systems and introduced a range of key technologies including AI, Kubernetes, Kafka, ELK, Prometheus, and more.
- BlueCrest is committed to providing an inclusive environment for its workforce.
Equal Opportunity
- As an employer, we provide equal opportunities to all people regardless of their gender, marital or civil partnership status, race, religion or ethnicity, disability, age, sexual orientation or nationality.