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Langgraph Jobs in Remote, OR (NOW HIRING)

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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 Remote, OR? For Langgraph jobs in Remote, OR, the most frequently searched job titles are:
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Langgraph jobs near you
Infographic showing various Langgraph job openings in Remote, OR as of June 2026, with employment types broken down into 91% Full Time, 3% Part Time, and 6% Contract. Highlights an 74% Physical, 4% Hybrid, and 22% Remote job distribution.
Senior Principal, AI Software Engineer- Agentic & Industry Solutions - Full Time Role

Senior Principal, AI Software Engineer- Agentic & Industry Solutions - Full Time Role

Technology Management Solutions

OR • Remote

$205K - $360K/yr

Contractor

Medical, Dental, Vision, Retirement

Posted 2 days ago

Job description

Job Description

Role: Senior Principal, AI Software Engineer- Agentic & Industry Solutions

Location- TX (Remote)

Role Type: Fulltime

Salary: $205200.00 - $360800.00 per yearly

Job Description

Be the one building AI-powered experiences where they matter most.

Senior Principal, AI Software Engineer- Agentic & Industry Solutions

Qualifications:

Bachelor's degree in Computer Science, Engineering, Artificial Intelligence, Data Science, or related discipline; Master's degree preferred

10+ years of experience in software engineering, solution architecture, enterprise integration, or cloud-native application development

5+ years of experience designing and implementing AI, Conversational AI, automation, or workflow orchestration solutions

Strong hands-on development experience building scalable enterprise applications

Proven ability to move solutions from concept and prototype through production deployment

Demonstrated technical leadership skills and ability to mentor engineers and architects

Strong communication and stakeholder engagement skills with ability to collaborate across Product, Engineering, and Strategic Customer teams

Experience building Agentic AI platforms, copilots, virtual agents, digital assistants, or intelligent automation solutions

Experience creating reusable solution accelerators, frameworks, and industry-specific assets

Understanding of industry processes within Financial Services, Healthcare, Insurance, Retail, Telecommunications, or Public Sector is a plus

Contributions to technical communities, open-source projects, patents, or innovation initiatives is a plus

Candidates must have willingness to travel as necessary; a valid passport is required

Technical proficiency in the following is not necessary, but a plus:

- Genesys Cloud Architecture, AI Studio, Copilot, Architect, Journey Management, Experience Orchestration, APIs and Event Frameworks

- Multi-Agent Systems, AI Skills and Agent Development, LLM Integration, RAG Architectures, Knowledge Systems, AI Workflow Automation

- AI Frameworks such as LangGraph, CrewAI, Semantic Kernel, LangChain, AutoGen, OpenAI APIs, Anthropic APIs, AWS Bedrock

- Python, JavaScript/TypeScript, REST APIs, Event-Driven Architectures, Microservices, Cloud platforms (AWS, Azure, Google Cloud)

- Expertise with RAG architectures, vector databases, knowledge orchestration, and enterprise search solutions

- Experience integrating AI solutions with CRM, ERP, Service Management, and enterprise workflow platforms

Note

Purpose:

The Principal Architect and AI Engineer - Agentic & Industry Solutions is a highly technical, hands-on leader responsible for designing, building, and scaling transformative AI-powered solutions on Genesys Cloud. Working within the Innovation Solutions organization, this role drives the development of reusable Agentic AI capabilities, industry-specific solution accelerators, and intelligent workflow automation that enable organizations to fundamentally transform customer and employee experiences. The Principal Architect and AI Engineer provides technical leadership and expertise across architecture, development, and solution delivery, collaborating with Product, Engineering, Strategic Customers, Industry SMEs, and Technology Partners to convert emerging AI technologies into scalable, market-leading solutions.

Benefits:

- Medical, Dental, and Vision Insurance.

- Telehealth coverage

- Flexible work schedules and work from home opportunities

- Development and career growth opportunities

- Open Time Off in addition to 10 paid holidays

- 401(k) matching program

- Adoption Assistance

- Fertility treatments

Additional Information

All your information will be kept confidential according to EEO guidelines.

Apply