Senior AI Engineer
Tasks
- Architect agent workflows
- Build RAG services
- Build Text-to-SQL solutions
- Collaborate across engineering and product teams
- Contribute to stack decisions and tradeoffs
- Deploy AI services on AWS or Azure
- Design implement and operate cloud native APIs
- Develop MCP servers for agents
- Ensure end-to-end observability
- Establish safety and quality controls
- Implement CI/CD pipelines
- Industrialize GenAI prototypes
- Participate in code reviews and mentoring
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 Bedrock | AWS ECS | AWS ECS Fargate | AWS EKS | AWS Lambda | AWS Secrets | AWS Secrets Manager | Amazon RDS | Amazon S3 | Azure AKS | Azure API | Azure API Management | Azure Cosmos | Azure Cosmos DB | Azure Functions | Azure Key Vault | Azure OpenAI | Azure PostgreSQL | Azure Storage | CI/CD | Caching | Cosmos DB | Databricks | Docker | ECS Fargate | Embeddings | Error Handling | FastAPI | FastMCP | GRPC | GitHub Actions | Infrastructure as Code | Injection defenses | Key Vault | Kubernetes | LLMs | Langchain | Langfuse | Langgraph | Langsmith | MLflow | Model Context Protocol | Monitoring | OAuth2 | OpenAPI | OpenID Connect | OpenSearch | OpenTelemetry | PGVector | PostgreSQL | PydanticAI | Python | Reliability Engineering | Reranking | Retrieval-Augmented Generation | Rédaction | Secrets Manager | Streaming | Terraform | Testing | Text-to-SQL | Tool-Calling | Vector Search | “as-code”
Education
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