Agentic AI Engineer and Lead

Overview

Hybrid
$60 - $70
Contract - W2
Contract - Independent
Contract - 12 Month(s)

Skills

Adaptability
Artificial Intelligence
Conflict Resolution
Cost Reduction
Decision-making
Generative Artificial Intelligence (AI)
Management
Operational Efficiency
Orchestration
POC
Pivotal
Problem Solving
Prototyping
Real-time
Reasoning

Job Details

Agentic AI Engineer and Lead Total 4 roles

We have 2 in Dallas, TX and 1 Lead and Developer in Basking NJ.

All are hybrid roles and need urgent attention.

Visa: EAD, GCEAD, and TN

Primary - LangGraph, ReAct, LangChain, LlamaIndex, Python

Google Cloud Platform, Google Spanner/Neo4j, CrewAI, AutoGen, OpenAI

JD:
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
    • 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

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.
  1. Driving AI Innovation & Research
  • Leadcutting-edge AI research in Agentic AI, LangGraph, LLM Orchestration, and Self-improving AI Agents.
  • Stay ahead of advancements in multi-agent systems, AIplanning, and goal-directed behavior, applying best practices to enterprise AI solutions.
  • Prototype and experiment with self-learning AIagents, enabling autonomous adaptation based on real-time feedback loops.
  1. AI Strategy & Business Impact
  • Translate AgenticAI capabilities into enterprise solutions, driving automation, operational efficiency, and cost savings.
  • LeadAgentic AI proof-of-concept (PoC) projects that demonstrate tangible business impact and scale successful prototypes into production

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

About Nexora business solutions LLC