ZipRecruiter

Log In

1

Langgraph Jobs in Virginia (NOW HIRING)

Accenture Federal Services

AI Engineer

Arlington, VA · On-site

Leverage tools and frameworks such as LangGraph, Semantic Kernel, vLLM, Ollama, and Ray for scalable AI solutions * Integrate with NVIDIA GPU ecosystems and vector databases to enhance AI performance ...

Accenture Federal Services

AI Engineer

Arlington, VA · On-site

Leverage tools and frameworks such as LangGraph, Semantic Kernel, vLLM, Ollama, and Ray for scalable AI solutions * Integrate with NVIDIA GPU ecosystems and vector databases to enhance AI performance ...

Frontier Technology Inc.

AI/ML Engineer

Chesapeake, VA · On-site +1

Contribute to agent-based applications using frameworks like LangGraph, AutoGen, CrewAI, or DSPy. * Integrate AI services into real-world systems via APIs, event-driven workflows, or UI copilots.

Ekcel Technologies Inc

AI engineer

Reston, VA · On-site

LangChain, LangGraph, Amazon Bedrock Agents Create multi-agent workflows and orchestration frameworks. Integrate agents with enterprise applications and APIs. Build human-in-the-loop workflows for ...

Hexaware Technologies, Inc

AI Engineer

Reston, VA · On-site

LangChain, LangGraph, Amazon Bedrock Agents * Create multi-agent workflows and orchestration frameworks. * Integrate agents with enterprise applications and APIs. * Build human-in-the-loop workflows ...

Rohirrim, Inc.

Senior AI Engineer

Mclean, VA · On-site

$105K - $145K/yr

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

Mclean, VA

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 ...

Deloitte

Oracle Gen AI Manager

Rosslyn, VA

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 ...

Deloitte

Oracle Gen AI Manager

Arlington, VA · On-site

You will help organizations improve automation, insight, and operational efficiency while applying emerging technologies such as Microsoft Copilot, Google Cloud Agent Space, LangGraph, Glean, and ...

next page

Showing results 1-20

All JobsLanggraph JobsLanggraph Jobs in Virginia

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 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 July 2026, with employment types broken down into 56% Full Time, 6% Part Time, and 38% Contract. Highlights an 92% In-person, 3% Hybrid, and 5% Remote job distribution.
AI Engineer

AI Engineer

Accenture Federal Services

Arlington, VA • On-site

Other

Posted 2 days ago

Accenture Federal Services rating

8.4

Company rating: 8.4 out of 10

Based on 19 frontline employees who took The Breakroom Quiz

51st of 454 rated business services

Job description

The work

As an AI Engineer in this role, you will drive the operationalization of advanced AI and agentic AI systems within production mission environments. Your work will center on implementing a modern Hub-and-Spoke architecture designed to accelerate enterprise AI adoption, support mission-critical applications, and enable robust AI governance.

You will be responsible for integrating AI solutions with DevSecOps, data engineering, platform engineering, and cybersecurity practices, ensuring seamless delivery and continuous monitoring of scalable AI-powered software. Your contributions will directly impact the deployment of agentic AI systems, orchestration frameworks, and operational workflows tailored to complex, real-world missions.

Key responsibilities:

  • Design, develop, and operationalize AI and agentic AI systems for production mission environments
  • Implement and optimize AI/ML production engineering workflows, including LLMOps and MLOps best practices
  • Architect and deploy Retrieval-Augmented Generation (RAG) solutions and AI orchestration frameworks
  • Manage Kubernetes-based AI deployments and ensure seamless integration with OpenAI-compatible APIs
  • Develop and maintain Python-based AI applications, focusing on GPU inference optimization
  • Leverage tools and frameworks such as LangGraph, Semantic Kernel, vLLM, Ollama, and Ray for scalable AI solutions
  • Integrate with NVIDIA GPU ecosystems and vector databases to enhance AI performance and scalability
  • Collaborate with cross-functional teams in AI, DevSecOps, data engineering, platform engineering, and cybersecurity
  • Support enterprise AI governance, continuous monitoring, and observability for mission-critical applications
  • Contribute to the delivery of scalable, secure, and reliable AI software within a modern Hub-and-Spoke architecture
  • Participate in the integration of operational workflows to accelerate AI adoption and mission impact

Here's what you need:

  • Experience AI/ML production engineering, LLMOps or MLOps, and the deployment of Retrieval-Augmented Generation (RAG) architectures.
  • Familiarity with Kubernetes-based AI deployments, OpenAI-compatible APIs, and Python development 
  • Experience in GPU inference optimization and working within NVIDIA GPU ecosystems

Nice to have:

  • Exposure to tools such as LangGraph, Semantic Kernel, vLLM, Ollama, Ray, and vector databases 
  • Experience in integrating observability, cybersecurity, and scalable software delivery into AI platforms will help you succeed in supporting the continuous evolution and governance of enterprise AI systems

Eligibility requirements:

  • US Citizen 
  • An active TS/SCI federal security clearance is required

What Accenture Federal Services employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

Apply