Senior AI Engineer
Tasks
- Build LLM powered backend pipelines
- Build MCP Model Context Protocol servers
- Build and operate AI evaluation and monitoring systems
- Build single and multi agent production systems
- Deploy AI services on AWS
- Design agentic systems
- Develop agentic workflows
- Develop prompt engineering and tool use patterns
- Implement observability and structured tracing
- Implement secure schemas and role based permissions
- Integrate LLM microservices and APIs
- Test and evaluate offline and online agent performance
Perks/Benefits
- Charity donation matching
- Complimentary office amenities
- Flexible working hours
- Health and fitness subsidy
- Hybrid work model
- Paid training
- Team and social events
- Volunteering days
- Work abroad
Skills/Tech-stack
AWS | AWS Bedrock | Agent systems | Bedrock AgentCore | Databricks | FastAPI | FastMCP | Fine Tuning | GRPC | Kubernetes | LLM | Langchain | Langfuse | Langgraph | Langsmith | Model Context Protocol | Multi-Agent | Multi-Agent Systems | Observability | PostgreSQL | Prompt engineering | Python | Retrieval-Augmented Generation | SQLAlchemy | Snowflake | Structured Logging | Tool use
Education
Roles
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