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Langgraph Jobs in Reston, VA (NOW HIRING)

Accenture Federal Services

AI Engineer

Alexandria, VA · On-site

$203.40K/yr

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

$116.90K - $243.10K/yr

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

$100.20K - $203.40K/yr

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 ...

Booz Allen Hamilton

Agentic AI Engineer

Washington, DC

$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 ...

Accenture Federal Services

AI Engineer

Alexandria, VA · On-site

$243.10K/yr

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 ...

Booz Allen Hamilton

Agentic AI Engineer

Washington, DC

$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 ...

Deloitte

Oracle Generative AI Manager

Mclean, VA · On-site

Knowledge of modern AI frameworks (LangChain, LangGraph, NVIDIA NIM, Hugging Face). * Proven track record of leading AI/ERP transformation programs in large enterprises. * Strong communication skills ...

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Langgraph information

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 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 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 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 Reston, VA? For Langgraph jobs in Reston, VA, the most frequently searched job titles are:
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What cities near Reston, VA are hiring for Langgraph jobs? Cities near Reston, VA with the most Langgraph job openings:
Langgraph jobs near you

AI / ML Subject Matter Expert (SME)

HRC Global Services

Reston, VA • On-site

Full-time

Posted 14 days ago

Job description

AI / ML Subject Matter Expert (SME)

Job Title: AI / ML SME – Generative AI & Advanced ML
Location: Remote / Hybrid (U.S.)
Employment Type: Full-Time

About the Opportunity:
Join a cutting-edge team driving AI innovation across enterprise systems. This role focuses on building scalable AI/ML solutions including Generative AI, LLMs, and advanced data pipelines.

Key Responsibilities:

  • Design and deploy AI/ML models including LLMs and RAG-based systems
  • Lead development of intelligent automation solutions
  • Collaborate across teams to build scalable AI platforms
  • Implement ML pipelines, CI/CD, and MLOps frameworks
  • Guide stakeholders on AI adoption and best practices

Required Skills:

  • 5+ years in AI/ML / Data Science / ML Engineering
  • Strong expertise in Python, SQL, and ML frameworks
  • Experience with cloud platforms (AWS / Azure / GCP / Databricks)
  • Hands-on experience with LLMs, RAG, Generative AI
  • Experience with Git, CI/CD, and model deployment

Advanced Requirements:

  • Experience with Hugging Face, LLaMA, LangChain or similar
  • Knowledge of model tuning, experimentation, and evaluation
  • Strong understanding of ML lifecycle and data pipelines

Nice to Have:

  • Experience with Agentic AI (AutoGen, LangGraph, CrewAI)
  • Knowledge graphs / federated learning
  • Research / publications in AI

Clearance: Public Trust (or eligible)

Hashtags:
#AI #MachineLearning #GenerativeAI #LLM #LangChain #Databricks #MLOps #CloudAI #TechLeadership #Hiring