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Langgraph Jobs in Virginia (NOW HIRING)

Raas Infotek LLC

Senior AI/ML Engineer GenAI & LLM

Richmond, VA · On-site

$103K - $142K/yr

Work with frameworks such as LangChain and LangGraph to build LLM-based applications and agentic workflows. * Develop and integrate REST APIs and backend services for AI/ML applications. * Implement ...

New

Phase2 Technology

Agentic AI Engineer

Mclean, VA · On-site

$99 - $225/hr

Design and implement intelligent agent architectures that can reason, plan, and take actions using LangChain, LangGraph, and AutoGen. * Develop and deploy multi‑agent systems using Model Context ...

Medium

AI Engineer

Richmond, VA · On-site

$100 - $130/hr

Build agent harnesses in Python using LangChain and LangGraph, including tool‑calling, structured outputs (Pydantic/JSON schema), retries, streaming, and memory * Package agent harnesses for the ...

Rohirrim, Inc.

Senior AI Engineer

Mclean, VA · On-site

$120 - $150/hr

Design and implement agentic orchestration using frameworks such as LangGraph, AutoGen, CrewAI, or custom-built solutions tailored to Rohirrim's platform requirements. * Develop tool-using, reasoning ...

Deloitte

Oracle Gen AI Manager

Rosslyn, VA · On-site

Experience with LangChain, LangGraph, NVIDIA NIM, or Hugging Face * Experience leading AI or ERP transformation programs for large enterprises The wage range for this role takes into account the wide ...

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All JobsLanggraph JobsLanggraph Jobs in Virginia

Langgraph information

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 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 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 popular job titles related to Langgraph jobs in Virginia?

For Langgraph jobs in Virginia, the most frequently searched job titles are:

What job categories do people searching Langgraph jobs in Virginia look for?

The top searched job categories for Langgraph jobs in Virginia are:

What cities in Virginia are hiring for Langgraph jobs?

Cities in Virginia with the most Langgraph job openings:

Langgraph jobs near you
Infographic showing various Langgraph job openings in Virginia as of August 2026, with employment types broken down into 1% Internship, 83% Full Time, 11% Part Time, and 5% Contract. Highlights an 77% Physical, 6% Hybrid, and 17% Remote job distribution.

Fulltime Java Full Stack Developer with AI

Argyllinfotech

Varina, VA • On-site

$51.75 - $66.75/hr

Full-time

Posted 3 days ago

New

Job description

Job title: Fulltime Java Full Stack Developer with AI
Location: McLean, VA
Work Model: Onsite/Remote (fulltime with implementation)
Experience: 9+ Years
 
Client: Confidential (at the time of interview candidate will get to know) 
 
Mandatory Requirements
  • LinkedIn profile must be established before 2019.
  • Candidate must provide a valid I-94.
  • Candidate must provide a valid passport document.
End-Client References — Mandatory
  • Candidates must provide 7 years of end-client references.
  • End-client references are mandatory.
  • Profiles without valid end-client references will be rejected by the client.
Must-Have Technical Skills
  • Java 8+
  • Spring Boot
  • Microservices
  • REST APIs
  • Angular / ReactJS
  • AWS
  • Docker
  • Kubernetes
  • Python
  • LangChain
  • LangGraph
  • JPA / Hibernate
  • PostgreSQL
  • Jenkins
  • Git
  • Maven / Gradle
AI Experience
  • Hands-on experience developing AI-powered applications
  • Experience with LLM workflows
  • Strong experience with LangChain and LangGraph
  • Experience with multi-step AI agent orchestration
Nice-to-Have Skills
  • OAuth / Ping Identity
  • Apigee
  • Istio
  • ELK Stack
  • MongoDB
  • GraphQL
  • Messaging Systems
  • Unix / Python
Ideal Candidate
  • Strong communication skills
  • Self-starter
  • Strong problem-solving abilities
  • Enterprise application development experience
  • Cloud and DevOps experience