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Langgraph Jobs in Georgia (NOW HIRING)

Insight Global

AI Engineer

Atlanta, GA · On-site +1

... with LangGraph or comparable; or LLM fine-tuning. • Proficient in Python and comfortable working with async code, data pipelines, and REST APIs. • Exposure to evaluation methodology for LLM ...

Worth AI

Senior Agentic (AI) Engineer

Atlanta, GA · On-site +1

$100K - $138K/yr

Architect agent graphs in LangGraph (or comparable - CrewAI, AutoGen, Claude Agent SDK) with explicit state, durable execution, retries, and safe fallbacks. * Build the retrieval layer powering our ...

Conflux Systems

Sr. Data Engineer

Atlanta, GA · On-site

$110K - $132K/yr

... LangGraph and RAG DB (for advanced data workflows) Qualifications • Bachelor's degree in computer science, Information Systems, or related field. • 2-3 years of experience in data engineering or ...

Caresoft Inc.

Sr. Data Engineer

Atlanta, GA · On-site

$62 - $66/hr

Familiarity with LangGraph and RAG DB concepts. Understanding of ETL/ELT pipelines and data warehousing concepts. Nice to have: Knowledge of CI/CD automation with Azure DevOps. Familiarity with data ...

Ubertal Inc

Senior Data Engineer

Atlanta, GA · On-site

LangGraph and RAG DB (for advanced workflows) Required Qualifications * Bachelor's degree in Computer Science, Information Systems, or related field. * 3-5 years of experience in data engineering or ...

Invesco

Principal Data Scientist, SIP

Atlanta, GA · On-site

Using tools such as Copilot Studio, LangGraph, Cortex, and AgentCore, you will create multi-agent workflows, develop evaluation frameworks, and lead AI initiatives from concept to production. This ...

Invesco

Principal Data Scientist, SIP

Atlanta, GA · Hybrid

Using tools such as Copilot Studio, LangGraph, Cortex, and AgentCore, you will create multi-agent workflows, develop evaluation frameworks, and lead AI initiatives from concept to production. This ...

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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 Georgia?

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

What job categories do people searching Langgraph jobs in Georgia look for?

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

What cities in Georgia are hiring for Langgraph jobs?

Cities in Georgia with the most Langgraph job openings:

Langgraph jobs near you
Infographic showing various Langgraph job openings in Georgia as of August 2026, with employment types broken down into 1% Internship, 86% Full Time, 3% Part Time, and 10% Contract. Highlights an 77% Physical, 6% Hybrid, and 17% Remote job distribution.

Integration Engineer - Fullstack Python (AI Agents, LangGraph, Context Engineering)

Diversity Nexus

Atlanta, GA • On-site

Full-time

Re-posted 16 days ago

Job description

Job Summary:
Diversity Nexus is seeking a talented and driven Integration Engineer with a strong fullstack Python background to join their AI solutions team. In this role, you will be responsible for building, integrating, and optimizing intelligent systems leveraging AI agents and advanced context engineering techniques.
Responsibilities:
• Design, develop, and maintain end-to-end Python applications that interface with AI agents and backend services, ensuring robust, scalable, and maintainable codebases.
• Implement and orchestrate autonomous and semi-autonomous AI agents, connecting them with APIs, data sources, and user-facing interfaces.
• Leverage the LangGraph framework to construct, visualize, and manage complex conversational flows and agent interactions.
• Architect and implement systems for dynamic context management, memory, and prompt engineering to optimize agent behavior and user experience.
• Integrate machine learning models, vector databases, and third-party services, ensuring seamless interoperability across components.
• Work closely with cross-functional teams to define requirements, propose technical solutions, and drive successful project delivery.
• Develop automated tests, monitor system performance, and continually refine integration points for reliability and efficiency.
Qualifications:
Required:
• Proven experience with full stack Python development (FastAPI, Flask, Django, React/Vue/Angular, SQL/NoSQL databases).
• Hands-on experience building and integrating AI agents (LLMs, RAG, multi-agent systems) in production environments.
• Familiarity with the LangGraph framework and agent orchestration patterns.
• Deep understanding of context engineering, including retrieval-augmented generation, prompt design, and session management.
• Experience with cloud platforms (AWS, GCP, Azure), containerization (Docker), and CI/CD pipelines.
• Strong problem-solving skills, attention to detail, and a collaborative mindset.
Preferred:
• Knowledge of advanced ML model serving, vector search, or knowledge graph integration.
• Experience with modern front-end frameworks and data visualization tools.
• Contributions to open-source AI or agent frameworks.
Company:
Diversity Nexus provides workforce inclusion staffing, payrolling, and supplier diversity solutions for large enterprises. Founded in , the company is headquartered in Princeton, USA, with a team of 201-500 employees. The company is currently Growth Stage.

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