Agentic AI

Agentic AI

Location:

Tampa, FL, Dallas, TX or Basking Ridge, NJ||Edison, NJ – 3 days Hybrid

Only 7+ years of experience candidate

Primary - Lang Graph, ReAct, Lang Chain, Llama Index, Python

Secondary - GCP, Google Spanner/Neo4j, CrewAI, Auto Gen, OpenAI

The Agentic AI 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 Lang Graph, 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.

Architecting & Scaling Agentic AI Solutions

· Design and develop multi-agent AI systems using Lang Graph 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.

Hands-On Development & Optimization

· Develop and optimize agent orchestration workflows using Lang Graph, 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.

Driving AI Innovation & Research

· Lead cutting-edge AI research in Agentic AI, Lang Graph, 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.

AI Strategy & Business Impact

· 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