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Langgraph Jobs in Rochester, NY (NOW HIRING)

RAG patterns and agentic frameworks (LangGraph); Python web/API development (FastAPI, Flask, Django) Local AI model stacks (vLLM, LiteLLM, Ollama); reverse proxies (Caddy, Nginx, Traefik); vector ...

Knowledge of agentic AI frameworks (LangChain, LangGraph, AutoGPT, CrewAI, etc.) * Experience with vector databases and RAG architecture * Familiarity with prompt engineering techniques and LLM fine ...

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 Rochester, NY? For Langgraph jobs in Rochester, NY, the most frequently searched job titles are:
What job categories do people searching Langgraph jobs in Rochester, NY look for? The top searched job categories for Langgraph jobs in Rochester, NY are:
What cities near Rochester, NY are hiring for Langgraph jobs? Cities near Rochester, NY with the most Langgraph job openings:
SR Software Engineer (Data) - Remote, US

SR Software Engineer (Data) - Remote, US

ITX Corp

Rochester, NY • Remote

Other

This job post has expired today. Applications are no longer accepted.


Job description

Salary: $96,000 to $129,000

Join Our Team as a Senior Software Engineer with Data Skills for Agentic AI Systems!


We are looking for a Senior Software Engineer with a strong focus onData and experience building infrastructure for LLM-powered applications and agent-based systems. In this role, you will work on RAG pipelines, agent workflows, and memory systems that allow AI agents to reason, retrieve information, and interact with complex tasks.

You will collaborate with engineers building intelligent agents and help design the data pipelines, evaluation frameworks, and orchestration workflows that support reliable and scalable AI systems.


Note: This opening is only available for candidates based in the United States of America. Applications from other locations will not be considered for the role.


What You'll Do:

  • Design and maintain ETL pipelines that process and classify unstructured data for Retrieval-Augmented Generation (RAG) systems.
  • Support the development of agent-based architectures using reasoning and acting patterns such as ReAct.
  • Build and maintain agent workflows using node-based orchestration frameworks such as LangGraph, including hierarchical and state-machine-based execution.
  • Design and implement agent memory systems, including short-term event memory and long-term memory strategies such as summarization, semantic memory, episodic memory, and user preference storage.
  • Develop system prompts and intent-handling prompts that support reliable agent interactions.
  • Create evaluation tests, datasets, and performance benchmarks to measure and improve LLM agent behavior, including ReAct-based agents.
  • Build tools that allow LLM agents to interact with external systems and services.
  • Apply best practices around guardrails, prompt security, input sanitization, and safe handling of user-generated content.
  • Collaborate closely with engineers across the team and provide guidance to less experienced developers when needed.


What We're Looking For:

  • Experience building RAG pipelines or ETL workflows for unstructured documents.
  • Experience working with LLM-based systems or AI-powered applications.
  • Familiarity with agent architectures such as ReAct.
  • Hands-on experience with workflow orchestration frameworks such as LangGraph or similar node-based systems.
  • Experience implementing agent memory systems (e.g., AgentCore Memory API or similar), including both short-term and long-term memory strategies.
  • Experience writing system prompts and designing prompt interactions for LLM applications, including intent handling.
  • Experience evaluating and performance testing LLM agents, particularly within ReAct-style workflows.
  • Ability to generate evaluation datasets and test scenarios for agent-based systems.
  • Understanding of mapping user utterances to intents using RAG and/or LLM-based approaches.
  • Understanding of guardrails and safety mechanisms for LLM and agent systems.
  • Understanding of agent-specific threat vectors, including prompt injection, tool misuse, and unsafe memory access.
  • Familiarity with AWS environments and tools such as AWS CLI and STS.
  • Strong understanding of data pipelines and document processing for AI systems.


Nice to have:

  • Experience with LangGraph or other agent orchestration frameworks.
  • Experience building tools for tool-enabled LLM agents.
  • Experience working with hierarchical state machines or complex workflow orchestration patterns.
  • Experience designing evaluation frameworks or LLM benchmarking systems.
  • Experience working with AI agent security concepts or threat modeling.


ITXs Compensation Philosophy

Equality in compensation has been our practice since ITX started, in 1997.


ITX believes that market-based pay ensures fair and equitable compensation for our worldwide team members and pay that is based on the market, not on who has the best negotiation skills. At ITX, youll never discover that someone in the same job with the same experience makes more than you, or that there are pay gaps based on race, gender, disability, or age.

How do our team members experience market-based pay at ITX? We gather market data to benchmark each position in our candidates and team members locations and use these benchmarks for candidate offers and to perform regular compensation reviews for our team members. Youll never have to worry about asking for a pay raise again. At least once a year ITX automatically adjusts pay when the benchmark is higher than our team members compensation.


In Rochester, N.Y., home to ITXs headquarters, the pay range for a Senior Software Developer with Data Skills role is $96,000 to $129,000, depending on experience, specific skills and certifications, and education. Based on your location in the United States if you are in a place where the market for your role is higher or lower, this pay range could be 13% lower or 10% higher than the Rochester, N.Y. market.


ITX has team members in many countries, and we use the same methodology for determining pay for all our teammates. For candidates outside of the United States, we use local market data to determine the benchmark range for the Senior Software Engineer with Data Skills.


Do you have questions about ITXs compensation practices? Let us know! Were proud of how we do compensation at ITX and welcome the opportunity to share more.

This role was posted by ITX on June 30th, 2026.