Senior Gen AI Engineer
Tasks
- Add observability tracing and cost monitoring
- Architect autonomous LLM agents
- Build and maintain property graphs and RDF triplestores
- Build entity resolution and deduplication
- Build graph aware RAG pipelines
- Deploy workloads on cloud infrastructure
- Design knowledge graph systems
- Develop ontologies and entity relationship schemas
- Implement agent memory reflection and self correction
- Implement confidence scoring and provenance tracking
- Implement graph ingestion pipelines
- Implement tool use and function calling
- Integrate external data sources via APIs and streaming
- Integrate web scraping and OSINT sources
- Maintain evaluation harnesses for accuracy and hallucinations
- Optimize graph traversal queries
- Package agents as microservices
- Train and deploy graph neural networks
Perks/Benefits
Skills/Tech-stack
Amazon Neptune | Autogen | CI/CD | CrewAI | Cypher | Docker | Few-Shot Learning | Few-shot | GNN | Graph Neural Networks | GraphQL | Gremlin | JSON-LD | Java | Kafka | Kinesis | Knowledge graphs | Kotlin | Kubernetes | LLM Evaluation | LLM orchestration | Langchain | Langgraph | Llamaindex | Neo4j | Neural Networks | OWL | PGVector | Pinecone | Playwright | Prompt engineering | Python | RAG Pipelines | RDF | RDF-star | REST APIs | Retrieval-Augmented Generation | SPARQL | Scrapy | Semantic Kernel | Shacl | TigerGraph | Vector Databases | W3C PROV | Weaviate | Web Scraping
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
Roles
AI Engineer | Engineer | Gen AI Engineer | Software Engineer
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