Senior AI Engineer
Tasks
- Architect agent workflows
- Build text-to-sql and RAG services
- Collaborate with cross-functional teams
- Deploy AI services on AWS and Azure
- Design, implement, and operate cloud-native APIs and microservices
- Develop Model Context Protocol MCP servers
- Ensure end-to-end observability
- Establish safety and quality controls
- Implement CI/CD pipelines
- Industrialize and scale GenAI prototypes
- Promote continuous learning
Perks/Benefits
- Employer supported pension plan
- Extra paid holidays
- Flexible benefits
- Home-office allowance
- Hybrid work model
- Life, accident, and disability insurance
- Medical care
Skills/Tech-stack
API Gateway | API Management | AWS Lambda | AWS Secrets | AWS Secrets Manager | Amazon Bedrock | Amazon ECS | Amazon EKS | Amazon RDS | Amazon S3 | Azure Functions | Azure Key Vault | Azure Kubernetes | Azure Kubernetes Service | Azure OpenAI | Azure Storage | CI/CD | Content Guardrails | Databricks | Docker | Embeddings | FastAPI | FastMCP | GRPC | GitHub Actions | Infrastructure as Code | Key Vault | Kubernetes | Kubernetes Service | LLMs | Langchain | Langfuse | Langgraph | Langsmith | MLflow | Model Context Protocol | OAuth2 | OpenAPI | OpenID Connect | OpenSearch | OpenTelemetry | PGVector | PostgreSQL | PydanticAI | Python | RAG | REST | Rate Limiting | Secrets Manager | Structured Logging | Terraform | Vector Search | “as-code”
Education
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