Lead AI Engineer (Agentic Systems)
Tasks
- Build semantic caching and cost containment
- Create agent benchmarking frameworks
- Define shared tool use boundaries
- Design enterprise multi agent orchestration blueprints
- Design evaluation frameworks for non deterministic AI systems
- Ensure AI safety bias mitigation and data privacy compliance
- Evaluate and adopt agentic paradigms
- Guard against runaway autonomous loops
- Implement fallback mechanics
- Implement state management protocols for agent networks
- Lead LLMOps and AgentOps governance standards
- Mentor and upskill developers
- Orchestrate secure API workflows with enterprise data
Perks/Benefits
Skills/Tech-stack
AWS | Agent systems | AgentOps | Artificial Intelligence | Automated Evaluation | Azure | Cloud Computing | Cost Optimization | Generative AI | Google Cloud | Graph Databases | Hybrid retrieval | LLMOps | Language Models | Large Language Models | Microservices | Multi-Agent | Multi-Agent Systems | Neo4j | Secure APIs | Semantic Caching | Semantic routing | State management | Vector Search
Education
Roles
AI | AI Engineer | Engineer | Lead | Lead AI Engineer
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