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Langgraph Jobs in Raleigh, NC (NOW HIRING)

Berriehill Research

Senior AI Systems Engineer

Raleigh, NC · On-site +1

$92K - $126K/yr

Familiarity with large language model (LLM) APIs and orchestration frameworks such as OpenAI, Hugging Face, LangGraph, or LangChain. * Experience with model serving, inference optimization, or AI ...

Infosys

Gen AI / Agentic AI Lead

Raleigh, NC · On-site

$136K - $167K/yr

Responsibilities : • Design, develop, and deploy Gen AI applications using LLMs and agentic frameworks (e.g., LangGraph, AutoGen, Crew AI). • Fine-tune open-source and proprietary LLMs using ...

ARA

Senior AI Systems Engineer

Raleigh, NC · On-site

$92K - $126K/yr

Familiarity with large language model (LLM) APIs and orchestration frameworks such as OpenAI, Hugging Face, LangGraph, or LangChain. * Experience with model serving, inference optimization, or AI ...

Bandwidth Inc.

Applied AI Engineer

Raleigh, NC · On-site

$104K - $137K/yr

Preferred : • Experience with agentic frameworks such as LangChain, LangGraph, CrewAI, AutoGen, or similar. • Familiarity with corporate IT or infrastructure engineering environments ...

RELX Group plc

Senior Data Scientist II

Raleigh, NC · On-site

$104K - $174K/yr

Experience designing agentic workflows and reasoning strategies, with hands-on experience applying agent frameworks (e.g., LangChain, LangGraph, AutoGen) in real-world use cases. * Proficiency in ...

RELX

Senior Data Scientist III - Agentic AI

Raleigh, NC · Hybrid

$115K - $192K/yr

Experience designing agentic workflows and reasoning strategies, with hands-on experience applying agent frameworks (e.g., LangChain, LangGraph, AutoGen) in real-world use cases. * Proficiency in ...

RELX

Senior Data Scientist II

Raleigh, NC · Hybrid

$104K - $174K/yr

Experience designing agentic workflows and reasoning strategies, with hands-on experience applying agent frameworks (e.g., LangChain, LangGraph, AutoGen) in real-world use cases. * Proficiency in ...

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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 Raleigh, NC? For Langgraph jobs in Raleigh, NC, the most frequently searched job titles are:
What job categories do people searching Langgraph jobs in Raleigh, NC look for? The top searched job categories for Langgraph jobs in Raleigh, NC are:
What cities near Raleigh, NC are hiring for Langgraph jobs? Cities near Raleigh, NC with the most Langgraph job openings:
Langgraph jobs near you
Infographic showing various Langgraph job openings in Raleigh, NC as of June 2026, with employment types broken down into 96% Full Time, and 4% Contract. Highlights an 81% Physical, 5% Hybrid, and 14% Remote job distribution.

Senior AI Systems Engineer

Berriehill Research

Raleigh, NC • On-site, Remote

$92K - $126K/yr

Full-time

Posted 7 days ago

Job description

Essential Functions:

  • Lead the deployment, integration, and operational support of AI platforms, tools, and services, ensuring compatibility with existing systems and enterprise processes.
  • Design, implement, monitor, and optimize AI infrastructure, working with server, cloud, and platform engineering teams.
  • Operationalize machine learning workflows and support AI-enabled applications from development through production deployment and sustainment.
  • Build and maintain CI/CD and MLOps pipelines for model packaging, testing, deployment, rollback, and lifecycle management.
  • Implement infrastructure automation using scripting, Infrastructure as Code, and configuration management practices.
  • Provide ongoing technical support, troubleshooting, root cause analysis, and documentation for AI platforms and user-facing AI services.
  • Maintain observability across AI systems through logging, metrics, performance monitoring, alerting, and incident response practices.
  • Ensure security, compliance, and governance requirements are met, including participation in audits, vulnerability management, and secure architecture reviews.
  • Assess and implement system enhancements to improve performance, scalability, reliability, and cost efficiency.
  • Collaborate across divisions to support diverse AI initiatives and align technical implementations with mission and business objectives.
  • Evaluate emerging AI tools, frameworks, and infrastructure approaches for operational fit, supportability, and long-term value.
  • Develop and maintain technical documentation, runbooks, architecture diagrams, and operational procedures.

Experience and Skills Required:

  • Bachelor’s degree in computer science, Engineering, Information Technology, or a related STEM field with 8-10 years of engineering experience. 
  • 2+ years of experience supporting AI/ML platforms, MLOps workflows, model deployment, or AI-enabled infrastructure.
  • Strong coding and automation skills in Python, Bash, or similar scripting languages.
  • Experience with AI/ML frameworks and tooling such as PyTorch, Hugging Face, or similar ecosystems.
  • Proficiency with DevOps and MLOps practices, including CI/CD pipelines, Git-based workflows, containerization, and Kubernetes.
  • Experience deploying AI/ML models or AI services into operational environments, including containerized, cloud, or high-performance computing environments.
  • Familiarity with security frameworks and compliance standards such as NIST and CMMC.
  • Familiarity with AI security functionality in enterprise environments including OAuth
  • Strong communication skills and the ability to collaborate effectively across technical and non-technical teams.

Preferred:

  • Advanced degree or certifications related to AI or machine learning.
  • Experience integrating AI models into scientific workflows.
  • Familiarity with large language model (LLM) APIs and orchestration frameworks such as OpenAI, Hugging Face, LangGraph, or LangChain.
  • Experience with model serving, inference optimization, or AI platform tools such as MLflow, Kubeflow, vLLM, or similar.
  • Experience with simulations for scientific or engineering projects, particularly physical systems simulations.
  • Experience with GPU-based systems or running AI models in HPC environments.
  • Experience writing and deploying MCP Servers on Kubernetes
  • DoD experience
  • Secret Security Clearance – Active or Inactive

Education:

  • Bachelor’s degree in CS, Software Engineering or other IT-related field or equivalent experience

REMOTE WORK NOTICE: This position may be performed fully remote, hybrid, or onsite at an ARA office. Preference will be given to candidates located onsite in the Albuquerque, NM and Raleigh, NC area.

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