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Langgraph Jobs in Washington (NOW HIRING)

Tactical Edge

Agentic AI Engineer

Washington, DC · On-site

$150 - $210/hr

Design and build multi-agent systems using frameworks like LangGraph, CrewAI, or custom orchestration. * Implement tool-use, function calling, and agentic workflows that operate reliably in ...

New

Snowrelic Inc

Senior UI Developer

Mclean, VA · Remote

$61.50 - $79.50/hr

Experience with LangGraph, LangChain, or similar agent orchestration frameworks * Knowledge of semantic web technologies and knowledge graphs * Experience with A/B testing and user interaction ...

Software Guidance & Assistance

Data Engineer

Rockville, MD · On-site

$116K - $140K/yr

Stay informed of advances in LLM frameworks (LangGraph, Google ADK, AWS Strands) and emerging AI capabilities * Write clean, well-tested code; contribute to CI/CD Jenkins pipelines and infrastructure ...

Dataquad Inc.

GenAI Engineer

Rockville, MD · On-site

$116K - $140K/yr

LangChain, LangGraph, AWS Strands, or equivalent • Working knowledge of prompt engineering, RAG architectures, and context/memory management • Experience with foundation model APIs (Anthropic ...

Compunnel

AI QE Architect

Bethesda, MD · On-site

... such as LangGraph, AutoGen, and CrewAI. • Implement MCP-driven, context-aware automation and CI/CD decision intelligence. • Architect and maintain automation frameworks using Playwright and ...

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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 Washington?

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

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:

Langgraph jobs near you
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 engineer :: Hybrid Columbia, MD or Lislie, IL

Tek Inspirations LLC

Columbia, MD • On-site

$120K - $159K/yr

Other

Posted 2 days ago

New

Job description

From the manager, he wants full stack AI engineers. See below:

React/Next.js + TypeScript. A better summary of everything is:

Hands on senior AI Engineer + Google Cloud Platform (vertex)+ Gemini/ADK/LangGraph + React/Next.js/TypeScript (not just "familiar with", personally built)

Position title: Senior AI engineer

Location: Either Columbia, MD or Lislie, IL

Onsite: 4 days a week

Contract: 6-9 months to perm (they want to definitely convert)

Relocation: yes but must be onsite from day 1

Interview process: 2 video interviews (1 is a panel for 30-45 minutes) then second round is 30 minutes with manager

Must have:

  1. Google Cloud Platform (Google Cloud Platform) Experience
  1. Hands-on experience building and deploying solutions in Google Cloud Platform.
  2. Azure experience is acceptable in addition to Google Cloud Platform
  1. LLMs, Generative AI & RAG
  1. Experience leveraging Gemini, Azure OpenAI, and other Large Language Models.
  2. Strong hands-on experience implementing Retrieval-Augmented Generation (RAG) solutions.
  1. Agent Framework Experience
  1. Direct experience with Google ADK, LangGraph, or similar agentic AI frameworks.
  2. Building AI agents/bots
  1. Senior-Level, Hands-On Engineer
  1. 6+ years of experience (preferably 8+).
  2. Must be a "working tech lead" type of engineer who owns code and actively develops rather than just leading projects.

Position details

  • New project initiative beginning next week. Manager is looking to add an experienced senior-level AI engineer who can immediately contribute to development efforts and eventually grow into a technical leadership role. The position is expected to support a multi-year initiative
  • Top Must-Haves:
  • Design and develop AI applications and intelligent agents on Google Cloud Platform.
  • Develop AI-powered bots and automation solutions.
  • Implement and maintain RAG (Retrieval Augmented Generation) solutions.
  • Leverage Gemini, Azure OpenAI, and other large language models.
  • Build solutions using agent frameworks such as Google ADK and LangGraph.
  • Perform hands-on coding and development activities.
  • Collaborate with technical leads and architects to deliver AI initiatives.
  • Participate in code ownership, architecture discussions, and solution design.
  • Grow into a technical leadership role while remaining highly hands-on

This individual will be responsible for building AI-powered applications, bots, and agent-based solutions primarily within Google Cloud Platform environments. The team is developing AI solutions leveraging LLM technologies, RAG architectures, and agent frameworks to support ongoing enterprise AI initiatives. The project is expected to run for several years

Must Have

  • Google Cloud Platform (Google Cloud Platform) experience.
  • AI/ML engineering experience.
  • Google ADK framework experience.
  • LangGraph experience.
  • Experience leveraging LLMs.
  • Gemini experience.
  • Azure OpenAI experience.
  • RAG implementation experience.
  • Python development.
  • React or Next.js.
  • TypeScript.
  • Strong software engineering background.
  • Hands-on development experience building AI products.

Nice to Have

  • Experience leading development teams.
  • Agentic AI development experience.
  • Prior experience serving as a Tech Lead.
  • Experience architecting enterprise AI solutions.
  • Multi-cloud experience with Azure alongside Google Cloud Platform

Experience Required

  • 8+ years preferred (manager emphasized a very senior resource).
  • Must possess senior-level engineering maturity.
  • Candidate may currently be a Senior AI Engineer, Senior Software Engineer, or Working Tech Lead.
  • Looking for someone capable of operating as a Tech Lead while remaining hands-on with coding.

What Will Make Someone Successful?

  • Extensive hands-on AI development experience.
  • Strong Google Cloud Platform expertise.
  • Deep knowledge of LLMs, Gemini, Azure OpenAI, and RAG.
  • Ability to own code and development efforts independently.
  • Comfortable leading technical direction while still contributing code.
  • Strong communication and collaboration skills.
  • Ability to work effectively within the Covista PMO environment.

Previous Companies / Background Targets

Target candidates from organizations actively building:

  • Enterprise AI applications.
  • Conversational AI solutions.
  • Agentic AI platforms.
  • Cloud-native AI products on Google Cloud Platform or Azure.
  • LLM-based enterprise solutions. (Suggested based on stated technical requirements.)

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