AI Engineer
Tasks
- Build AI integrations using MCP
- Build production backend applications
- Build vector search and retrieval pipelines
- Design, build, deploy GenAI solutions
- Design, build, deploy ML solutions
- Develop agentic systems orchestration
- Implement evaluation for GenAI systems
- Implement observability logging monitoring debugging
- Implement privacy security guardrails for AI systems
- Implement retrieval augmented generation systems
- Integrate tools and external systems
- Troubleshoot production issues and improve reliability
Perks/Benefits
- N/A
Skills/Tech-stack
AWS | Agent Orchestration | Apache Spark | Azure | CI/CD | Chunking | Context Construction | Context engineering | Data Pipelines | Databricks | Debugging | Django | Docker | Embeddings | Evaluation | Experiment tracking | FastAPI | Flask | Generative AI | Google Cloud | Guardrails | Haystack | LLM API | Langchain | Langgraph | Logging | MCP | MLOps | Machine Learning | Model versioning | Monitoring | Multi Step Execution | NoSQL | Privacy | Prompt engineering | Python | RAG | Relational databases | Reranking | Retrieval Pipeline | Security | Tool use | Vector Database | Vector Search
Education
N/A
Roles
AI | AI Engineer | Engineer | Learning Engineer | Machine Learning Engineer
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