Lead Engineer – GenAI, Agentic AI, and Knowledge Graph Architect
Tasks
- Architect neuro symbolic AI solutions
- Build agentic AI systems
- Create multi agent orchestration and tool use
- Deploy scalable AI APIs for agent workflows
- Design graph data models ontologies taxonomies
- Develop graph queries and traversal patterns
- Ensure AI governance compliance observability
- Implement human-in-the-loop workflows
- Implement knowledge graph architectures
- Integrate LLMs and prompt engineering
- Integrate vector and graph databases
- Lead AI engineering mentorship and technical strategy
Perks/Benefits
- N/A
Skills/Tech-stack
Agent Orchestration | Agent memory | Agentic AI | Amazon Neptune | ArangoDB | CI/CD | ChromaDB | Cypher | Data Modeling | Data Pipelines | ETL | Evaluation | Experimentation | Function Calling | Governance | Graph Algorithms | Graph Data | Graph Data Modeling | Graph Databases | Graph Query | Graph Query Languages | GraphDB | Gremlin | Human-in-the-loop | JanusGraph | Knowledge graphs | Labeled Property Graphs | Language Models | Large Language Models | MLOps | Monitoring | Multi-Agent | Multi-agent orchestration | Neo4j | NoSQL | OWL | Observability | Ontologies | Persistent State | Planning | Prompt engineering | Property graphs | Python | Query languages | RDF | RDFS | Reasoning engines | Reflection | Routing | SPARQL | SQL | Semantic Technologies | Semantic Web | Shacl | Stardog | Task decomposition | The Loop | TigerGraph | Tool use | Vector Databases
Roles
AI Engineer | Engineer | GenAI Engineer | Lead | Lead AI Engineer | Learning Engineer | Machine Learning Engineer
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