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Langgraph Jobs in New Rochelle, NY (NOW HIRING)

LangChain & LangGraph * Prompt Engineering * Embeddings & Vector Databases * OpenAI / Azure OpenAI / AWS Bedrock * AI/ML application development * AWS or Azure * Strong technical leadership and ...

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Senior AI Developer

Manhattan, NY · On-site

$125K - $140K/yr

Leverage LangGraph's stateful graph execution model to build resilient, interruptible, and human-in-the-loop agentic workflows * Integrate LLM-powered agents with external APIs, databases, and ...

Leverage LangGraph's stateful graph execution model to build resilient, interruptible, and human-in-the-loop agentic workflows * Integrate LLM-powered agents with external APIs, databases, and ...

Develop RAG and LLM-based solutions using Python and LangChain/LangGraph. * Integrate AI solutions with enterprise applications and data sources. * Deploy and maintain AI applications on AWS.

LangGraph * Agent-Based AI Systems * Autonomous AI Agents * ReAct (Reasoning + Acting) * LLM Reasoning, Planning & Task Execution * Model Context Protocol (MCP) * Tool Calling & Tool Integration

In this role, you'll partner directly with customers to design, build, and deploy intelligent applications using Python, Langchain/LangGraph, and large language models. You'll bridge engineering ...

Deep expertise in LLM architectures, prompt engineering, and agentic frameworks (LangGraph, LangMem). * Hands-on experience with Azure OpenAI GPT-4/5, embedding models, and Azure cloud services.

GenAI Lead

Manhattan, NY · On-site

$184K/yr

The ideal candidate will have strong hands-on expertise in RAG, Python, LangChain, and LangGraph , along with experience delivering AI solutions in enterprise environments. Key Responsibilities

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AI Data Engineer

Manhattan, NY · On-site

$126K - $151K/yr

Python, Data Engineering, ETL/ELT, Data Pipelines, LLM Applications, Agentic AI, RAG, LangChain, LangGraph, LlamaIndex, Vector Databases, Kubernetes, Cloud Platforms (AWS/Azure/Google Cloud Platform ...

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Langgraph information

What is the difference between Langgraph vs Data Analyst?

AspectLanggraphData Analyst
Required CredentialsTypically requires knowledge of language processing and graph databasesUsually requires a degree in statistics, mathematics, or related fields
Work EnvironmentTech companies, AI research labs, data-driven organizationsBusiness, finance, healthcare, and marketing sectors
Industry UsageEmerging role in AI and NLP projectsEstablished role in data interpretation and reporting

While Langgraph focuses on language processing and graph database integration, Data Analysts primarily interpret and visualize data to support business decisions. Both roles require analytical skills, but Langgraph specialists often have a background in AI and NLP, whereas Data Analysts typically hold degrees in statistics or related fields.

What are the key skills and qualifications needed to thrive as a Langgraph engineer, and why are they important?

To thrive as a Langgraph engineer, you need a strong background in software engineering, proficiency in Python, and a solid understanding of AI/ML concepts, usually supported by a degree in computer science or a related field. Familiarity with machine learning frameworks (like TensorFlow or PyTorch), API integrations, and version control systems such as Git is essential. Effective problem-solving, collaboration, and clear communication are crucial soft skills for working with multidisciplinary teams and resolving complex issues. These capabilities are important because they enable the development, scaling, and maintenance of robust AI-driven applications using the Langgraph platform.

What is a Langgraph?

Langgraph is a framework designed to build, manage, and orchestrate complex workflows for large language models (LLMs). It allows developers to create directed graphs of language model prompts, tools, and custom logic, making it easier to design multi-step, stateful AI applications. Langgraph is especially useful for building conversational agents, automated workflows, and other applications that require LLMs to interact with data or tools in a structured way.

What are some common challenges faced by Langgraph developers when integrating their workflow with existing AI infrastructure?

Langgraph developers often encounter challenges when integrating their workflow with existing AI infrastructure, such as ensuring compatibility with various large language models and managing data flow across multiple APIs. Coordination with data engineers and machine learning specialists is crucial to align model outputs with business requirements, and adapting to rapidly evolving technologies can require continuous learning. Additionally, optimizing performance and maintaining security standards during integration are key considerations to ensure successful deployment.

What are popular job titles related to Langgraph jobs in New Rochelle, NY?

For Langgraph jobs in New Rochelle, NY, the most frequently searched job titles are:

What job categories do people searching Langgraph jobs in New Rochelle, NY look for?

The top searched job categories for Langgraph jobs in New Rochelle, NY are:

What cities near New Rochelle, NY are hiring for Langgraph jobs?

Cities near New Rochelle, NY with the most Langgraph job openings:

Infographic showing various Langgraph job openings in New Rochelle, NY as of June 2026, with employment types broken down into 93% Full Time, 3% Part Time, and 4% Contract. Highlights an 82% Physical, 3% Hybrid, and 15% Remote job distribution.

GenAI Lead

Thinklusive

Manhattan, NY • On-site

Other

Posted yesterday

New


Job description

Role: GenAI Lead

Location: New York City, NY
Experience: 12+ Years

Work Model: Hybrid 3 Days/Week Onsite

Job Description

Seeking an experienced GenAI Lead to design and deliver enterprise AI/ML solutions with strong hands-on expertise in Python, RAG, LangChain, and LangGraph.

Required Skills

  • Python
  • Generative AI / LLMs
  • RAG
  • LangChain & LangGraph
  • Prompt Engineering
  • Embeddings & Vector Databases
  • OpenAI / Azure OpenAI / AWS Bedrock
  • AI/ML application development
  • AWS or Azure
  • Strong technical leadership and client-facing skills

Responsibilities

  • Lead design and development of GenAI/LLM solutions.
  • Build RAG pipelines using LangChain/LangGraph.
  • Integrate LLMs, vector databases, and enterprise data.
  • Translate client requirements into AI solutions.
  • Lead technical discussions, architecture, code reviews, and mentoring.
  • Ensure solutions are scalable, secure, and production-ready.