Agentic AI Lead
Agentic AI Lead
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Job Description
Agentic AI Lead
Dallas Texas OR Tampa FL (Onsite)
1 Year
Job requirements
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- The Agentic AI Lead is a pivotal role responsible for driving the research development and deployment of semi-autonomous AI agents to solve complex enterprise challenges. This role involves hands-on experience with LangGraph leading initiatives to build multi-agent AI systems that operate with greater autonomy adaptability and decision-making capabilities. The ideal candidate will have deep expertise in LLM orchestration knowledge graphs reinforcement learning (RLHF/RLAIF) and real-world AI applications. As a leader in this space they will be responsible for designing scaling and optimizing agentic AI workflows ensuring alignment with business objectives while pushing the boundaries of next-gen AI automation.
Key Responsibilities:
1. Architecting & Scaling Agentic AI Solutions
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- Design and develop multi-agent AI systems using LangGraph for workflow automation complex decision-making and autonomous problem-solving.
- Build memory-augmented context-aware AI agents capable of planning reasoning and executing tasks across multiple domains.
- Define and implement scalable architectures for LLM-powered agents that seamlessly integrate with enterprise applications.
2. Hands-On Development & Optimization
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- Develop and optimize agent orchestration workflows using LangGraph ensuring high performance modularity and scalability.
- Implement knowledge graphs vector databases (Pinecone Weaviate FAISS) and retrieval-augmented generation (RAG) techniques for enhanced agent reasoning.
- Apply reinforcement learning (RLHF/RLAIF) methodologies to fine-tune AI agents for improved decision-making.
3. Driving AI Innovation & Research
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- Lead cutting-edge AI research in Agentic AI LangGraph LLM Orchestration and Self-improving AI Agents.
- Stay ahead of advancements in multi-agent systems AI planning and goal-directed behavior applying best practices to enterprise AI solutions.
- Prototype and experiment with self-learning AI agents enabling autonomous adaptation based on real-time feedback loops.
4. AI Strategy & Business Impact
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- Translate Agentic AI capabilities into enterprise solutions driving automation operational efficiency and cost savings.
- Lead Agentic AI proof-of-concept (PoC) projects that demonstrate tangible business impact and scale successful prototypes into production.
5. Mentorship & Capability Building
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- Lead and mentor a team of AI Engineers and Data Scientists fostering deep technical expertise in LangGraph and multi-agent architectures.
- Establish best practices for model evaluation responsible AI and real-world deployment of autonomous AI agents.
Required Skills & Experience
Strong hands-on experience with LangGraph and multi-agent AI development
Proficiency in LLM orchestration (LangChain LlamaIndex OpenAI Function Calling)
Expertise in reinforcement learning (RLHF RLAIF) and self-improving AI agents
Knowledge graph construction & RAG implementation for enhanced agent reasoning
Experience deploying AI agents in production (GCP)
Thanks & Regards
Naveen Vulupala
(An eVerified Participant)
1159 Sonora Court Suite 120
Sunnyvale California 94086
Employment Type
Full Time
