Senior Data Scientist
BetMGM
PythonSparkSQL
Data Scientist
Brillio
full-time
Posted on:
Location Type: Hybrid
Location: Edison • New Jersey • 🇺🇸 United States
Visit company websiteJob Level
Mid-LevelSenior
About the role
- 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.
- 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.
- 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.
- 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.
Requirements
- 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.
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
LangGraphmulti-agent AI systemsmemory-augmented AI agentsLLM orchestrationknowledge graphsvector databasesreinforcement learningagent orchestration workflowsretrieval-augmented generationself-learning AI agents
Soft skills
leadershipproblem-solvingadaptabilitycommunicationcollaborationresearchinnovationproject managementstrategic thinkingdecision-making
