Cloud & MLOps Engineer - Financial Services
Tasks
- Automate environments packaging testing deployments with CI CD
- Build and operate secure scalable ML LLM platforms
- Build and secure APIs and microservices
- Build automated training and inference pipelines
- Define SLOs alerting and incident response
- Document operations and enforce SDLC controls
- Engineer RAG pipelines
- Evaluate and govern models
- Harden runtime infrastructure with IaC
- Implement OAuth2 zero trust and API rate limiting
- Implement data and model versioning
- Ingest chunk and embed documents
- Manage secrets and implement RBAC network security
- Optimize vector store indexing retrieval caching
- Perform performance tuning and capacity planning
- Set up observability and monitoring dashboards
Perks/Benefits
- Access to new technologies
- Career support
- Client site flexibility
- Flexible working arrangements
- Lifestyle balance
- Training programs
Skills/Tech-stack
.Net Core | AI Search | AKS | API rate-limiting | App Service | Application Insights | Azure | Azure AI | Azure AI Search | Azure App | Azure App Service | Azure Container | Azure Container Registry | Azure DevOps | Azure Functions | Azure Key Vault | Azure Policy | Azure Storage | Bash | Bicep | CI/CD | Container Registry | Containers | DORA | DVC | Data Versioning | Embeddings | FastAPI | Gatekeeper | GitHub Actions | Grafana | GraphQL | IaC | Incident Response | JavaScript | Key Vault | Kubernetes | Langchain | MLflow | Node.js | OAuth2 | OPA | PGVector | Prometheus | Python | RAG | RBAC | Rate Limiting | React | Redis | SLO | Semantic Kernel | Terraform | Vector Databases | Zero Trust
Education
N/A
Roles
Cloud Engineer | Cloud) | DevOps | DevOps Engineer | Engineer | MLOps Engineer
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