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Langgraph Jobs in Georgia (NOW HIRING)

... 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 ...

AI Solution Architect

Atlanta, GA · On-site

$60.50 - $79.75/hr

Build AI solutions using LangChain, LangGraph, vector databases, prompt engineering, and AI orchestration frameworks. * Define enterprise AI governance, security, compliance, and Responsible AI best ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 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 cities in Georgia are hiring for Langgraph jobs? Cities in Georgia with the most Langgraph job openings:
Infographic showing various Langgraph job openings in Georgia as of July 2026, with employment types broken down into 57% Full Time, 5% Part Time, and 38% Contract. Highlights an 92% In-person, 3% Hybrid, and 5% Remote job distribution.

$90K - $110K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 22 days ago


Job description

Must Have Technical/Functional Skills
Job Description AI/ML Engineer (GenAI, RAG & Data Engineering)
We are seeking a highly motivated AI/ML Engineer with experience in designing, developing, and deploying Generative AI and Machine Learning solutions. The ideal candidate should possess strong expertise in Python, LLMs, RAG architectures, LangChain/LangGraph, PySpark, Airflow, and cloud technologies, along with hands-on experience building scalable AI-powered applications and data pipelines.
AI/ML & Generative AI(Primary Skill set)
NLP and Transformer Architectures
Large Language Models (LLMs)
Prompt Engineering
Retrieval-Augmented Generation (RAG)
Model Context Protocol (MCP)
Frameworks like LangChain, LangGraph
Python, SQL
Secondary Skill set
Exposure to Cloud Platforms(Azure/AWS)
Exposure to Modern Data platforms (Databricks, Snowflake)
Salary Range: $90,000- $110,000 a year
TCS Employee Benefits Summary:
Discretionary Annual Incentive.
Comprehensive Medical Coverage: Medical & Health, Dental & Vision, Disability Planning & Insurance, Pet Insurance Plans.
Family Support: Maternal & Parental Leaves.
Insurance Options: Auto & Home Insurance, Identity Theft Protection.
Convenience & Professional Growth: Commuter Benefits & Certification & amp; Training Reimbursement.
Time Off: Vacation, Time Off, Sick Leave & Holidays.
Legal & Financial Assistance: Legal Assistance, 401K Plan, Performance Bonus, College Fund, Student Loan Refinancing.
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