Senior GenAI Engineer
Tasks
- Architect end-to-end AI pipelines
- Build RAG pipelines for knowledge capture and curation
- Build automated evaluation pipelines and testing frameworks
- Collaborate with stakeholders product managers platform teams and data engineers
- Design develop and deploy scalable GenAI applications
- Develop AI powered copilots assistants and automation workflows
- Develop GenAI proof of concepts
- Implement multi-agent orchestration workflows
- Implement tracing telemetry observability and monitoring
- Improve reliability with retrieval optimization and AI safety mechanisms
- Integrate structured and unstructured enterprise data
- Optimize inference cost latency throughput and scalability
- Own AI systems from prototype to production
Perks/Benefits
- N/A
Skills/Tech-stack
AI Agents | API Development | AWS | Agent Orchestration | Distributed Systems | Docker | Embeddings | FastAPI | Fine Tuning | Inference Optimization | Kubernetes | LLM APIs | Langchain | Langgraph | LoRA | Microservices | Model Fine-tuning | Monitoring | Multi-Agent | Multi-agent orchestration | Observability | PEFT | Prompt engineering | Python | RAG | React | SQL | Snowflake | Streamlit | Telemetry | Tool-Calling | Vector Databases | Vector similarity
Education
N/A
Roles
Engineer | GenAI Engineer | Senior GenAI Engineer | Software Engineer
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