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Langgraph Jobs in Washington (NOW HIRING)

Sr. Software Engineer

Ashburn, VA · Hybrid

$125K - $165K/yr

Develop solutions using agent frameworks such as LangGraph, LangChain, Haystack, or similar technologies. * Implement modern AI architectures leveraging AWS services including Bedrock, SageMaker ...

Senior AI Software Engineer

Mclean, VA · On-site

$123K - $163K/yr

Python proficiency and familiarity with libraries and frameworks (uv, Pydantic, FastAPI, CrewAI, LangChain, LangGraph, Unstructured). * Demonstrated curiosity and practical experimentation with ...

Senior AI Software Engineer

Mclean, VA · On-site

$155 - $200/hr

Pythonproficiencyand familiarity with librariesand frameworks(uv,Pydantic,FastAPI,CrewAI,LangChain,LangGraph, Unstructured). * Demonstrated curiosity and practical experimentation with emerging AI ...

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 ...

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 ...

Senior AI Software Engineer

Mclean, VA

$123K - $163K/yr

Python proficiency and familiarity with libraries and frameworks (uv, Pydantic, FastAPI, CrewAI, LangChain, LangGraph, Unstructured). * Demonstrated curiosity and practical experimentation with ...

Senior AI Software Engineer

Mclean, VA · On-site

$123K - $163K/yr

Python proficiency and familiarity with libraries and frameworks (uv, Pydantic, FastAPI, CrewAI, LangChain, LangGraph, Unstructured). * Demonstrated curiosity and practical experimentation with ...

Applied AI Engineer

Arlington, VA · On-site

$159K - $263K/yr

Pydantic-AI, LangChain/LangGraph, CrewAI * Infra: Docker, Kubernetes; cloud platforms (AWS, GCP, Azure) * Experiment and artifact tracking: dataset/prompt/model versioning Security / Work Environment ...

Semantic Kernel, LangGraph, AutoGen, CrewAI, MCP, or equivalent frameworks. * NLP, sentiment analysis, classification, summarization, and knowledge management. Cloud & Platforms: * Microsoft Azure ...

Agentic AI Engineer

Mclean, VA · On-site

$99K - $225K/yr

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 ...

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 ...

Agentic AI Engineer

Bethesda, MD · 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 ...

Agentic AI Engineer

Washington, DC · On-site

$99K - $225K/yr

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 ...

Agentic AI Engineer

Bethesda, MD · On-site

$99K - $225K/yr

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 ...

Showing results 41-60

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 job categories do people searching Langgraph jobs in Washington look for?

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

What cities in Washington are hiring for Langgraph jobs?

Cities in Washington with the most Langgraph job openings:

Infographic showing various Langgraph job openings in Washington as of August 2026, with employment types broken down into 1% Internship, 87% Full Time, 1% Part Time, 2% Temporary, and 9% Contract. Highlights an 73% Physical, 6% Hybrid, and 21% Remote job distribution.

Senior AI Software Engineer-TS/SCI clearances (CI poly preferred)

Credence

Herndon, VA

$126K - $166K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 9 days ago


Job description

Overview

Join a team where innovation meets mission. Our AI, cloud, cyber, and modernization solutions save agencies thousands of hours, safeguard national security, and strengthen health and humanitarian missions worldwide. With 1,700+ team members, 1,500+ AI/data experts, and 100+ prime contracts, we deliver at scale and with purpose.

We've been recognized as a Top Workplace by the Washington Post for six straight years and named to the Inc. 5000 Fastest Growing Private Companies 13 of the past 14 years. Credence is a welcoming home for those looking to grow and contribute to positive change. We encourage all employees to expand beyond their boundaries, dive into important world-changing Federal challenges.

Position Summary

Credence has an immediate need for a Senior AI Software Engineer to join our growing AI and Automation practice. In this role, you will serve as a senior technical contributor responsible for designing, developing, and deploying advanced AI-driven solutions, including generative AI, LLM-powered applications, and agentic AI systems. You will collaborate with cross-functional engineering, data, cloud, and stakeholder teams to deliver scalable, secure, and mission-focused AI capabilities for federal clients, while helping guide technical direction, strengthen engineering practices, and mentor other engineers.

Responsibilities include, but are not limited to the duties listed below

  • Generative AI & LLM Solution Delivery
    Lead the design, development, prototyping, and refinement of AI-powered capabilities using generative AI, large language models, retrieval patterns, prompt/context engineering, and secure API integrations.
  • Agentic AI System Development
    Own end-to-end agentic AI development lifecycles, including model selection, agent design, tool/function calling, orchestration, response synthesis, evaluation, and deployment of reliable AI agents.
  • Senior Software Engineering Leadership
    Apply strong software engineering principles to design maintainable, testable, and scalable systems; conduct code reviews, establish technical patterns, and leverage AI-assisted development tools responsibly to accelerate delivery.
  • Cross-Functional Technical Collaboration
    Partner with data engineers, software engineers, data scientists, cloud engineers, and mission stakeholders to translate business and mission needs into operational AI and automation solutions.
  • Cloud Enablement & DevSecOps Integration
    Design and automate deployment workflows using Infrastructure as Code (IaC), CI/CD pipelines, containers, and cloud-native services to support secure, repeatable, and scalable AI delivery.
  • Production Monitoring & Optimization 
    Monitor AI systems post-deployment, perform performance tuning, and apply best practices for reliability and scalability.
  • Technical Rigor & Documentation 
    Write clean, well-documented code following industry and federal guidelines; support reproducible development.
  • Technical Mentorship & Continuous Improvement
    Stay current on emerging AI/ML trends, agentic frameworks, model capabilities, and engineering practices while mentoring team members and contributing to reusable standards, documentation, and technical design reviews.

Requirements

What You Bring

  • TS/SCI clearances Required (CI poly preferred).
  • Bachelor's or Master's in Computer Science, AI/ML, or a related field.
  • 7+ years of hands-on software engineering experience, including significant experience delivering AI/ML, generative AI, or LLM-powered solutions in production or production-like environments.
  • Experience building generative AI applications, working with LLMs, implementing tool/function calling, and applying model evaluation, prompt/context engineering, or retrieval-augmented generation approaches.
  • Experience designing or implementing agentic AI solutions using frameworks or platforms such as Agent2Agent Protocol, Bedrock Agents, Mastra, CrewAI, Strands, AgentCore, LangChain, or LangGraph.
  • Strong understanding of leading AI APIs and model platforms such as OpenAI, Anthropic, Gemini, Amazon Bedrock, and Google Vertex AI.
  • Proficiency in TypeScript and familiarity with key libraries and frameworks such as Nx, Next.js, Mastra, Vercel AI SDK, Playwright, Jest, and Vite.
  • Python proficiency and familiarity with libraries and frameworks (uv, Pydantic, FastAPI, CrewAI, LangChain, LangGraph, Unstructured).
  • Demonstrated curiosity and practical experimentation with emerging AI technologies, with a strong focus on responsible innovation and measurable mission impact.
  • Familiarity with CI/CD pipelines (GitLab CI)
  • Experience with VS Code and AI extensions such as Cline and Claude Code.
  • Strong communication skills and client-oriented mindset.

Preferred

  • Curious and experimental about the latest innovations in AI with an orientation toward the relentless pursuit of delivering mission impact.
  • Exposure to adjacent skillsets such as data engineering, data science, UI/UX, cloud engineering, and platform engineering to understand the entire software ecosystem.
  • Experience with IaC tools such as Terraform, Open Tofu, AWS CDK, or CloudFormation to deploy cloud native applications.
  • Knowledge of federal cybersecurity, RMF, FedRAMP, or regulatory frameworks.

Why This Role Matters

  • Real-World Impact- Your work will support defense and health agencies where AI solutions directly contribute to national security and public well-being.
  • Growth-Oriented Technical Leadership - Work with technical leaders, shape agentic AI delivery practices, and mentor team members while continuing to deepen your own expertise in advanced AI engineering.
  • Culture of Empowerment- You'll be part of a team that values innovation, trust, collaboration, and mission success.

 Salary Range: $155,000 - $200,000 annually. Actual compensation will be determined based on the selected candidate's experience, education, certifications, skills, and overall qualifications.

Benefits

  • Health Care Plan (Medical, Dental & Vision)
  • Retirement Plan (401k, IRA)
  • Life Insurance (Basic, Voluntary & AD&D)
  • Paid Time Off (Vacation, Sick & Public Holidays)
  • Family Leave (Maternity, Paternity)
  • Short Term & Long Term Disability
  • Training & Development
  • Wellness Resources