AI Engineer, Generative AI Agents
Tasks
- Automate operational workflows with AI agents
- Build and maintain LLM powered services and APIs
- Build client facing tools for voice and natural language queries
- Collaborate with cross-functional teams to deliver AI solutions
- Design and develop intelligent AI agents for intent recognition and query decomposition
- Develop evaluation harnesses and eval pipelines
- Develop standardized tooling protocols for agent integration
- Enable self service data access and analysis with AI agents
- Implement and optimize context engineering for short and long term memory
- Instrument services with logging tracing and metrics
- Integrate AI agents with internal and third-party systems
- Participate in agile development sprints
Perks/Benefits
Skills/Tech-stack
AWS Bedrock | Context engineering | Databricks | Error Handling | FastAPI | Intent detection | Knowledge graphs | Langgraph | Language Models | Large Language Models | Latency optimization | Logging | MCP | Metrics | Observability | Python | Query decomposition | RAG | Retrieval-Augmented Generation | Retry Mechanisms | Snowflake | Throughput Optimization | Timeouts | Token Usage Monitoring | Token usage | Tracing | Usage monitoring | Vector Databases | Webhooks
Education
Roles
AI | AI Engineer | AI Platform Engineer | Engineer | Generative AI Engineer | Platform Engineer
Regions
Countries
States
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