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Langgraph Jobs in Austin, TX (NOW HIRING)

Solution Architect (Austin)

Austin, TX · On-site

$62.50 - $82.25/hr

Today, our platform includes LangSmith (Observability, Evaluation, Deployment, Fleet, and Sandboxes), our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched ...

Responsibilities : • Design, develop, and maintain secure, scalable implementation of the Datalinx product. • Build AI-driven agentic solutions using frameworks like LangGraph and/or Autogen ...

Responsibilities : • Design, develop, and maintain secure, scalable implementation of the Datalinx product. • Build AI-driven agentic solutions using frameworks like LangGraph, designing ...

Responsibilities : • Design and implement multi-actor state machines using LangGraph, including loops, error-recovery paths, and human-in-the-loop checkpoints • Own the observability and ...

Design and implement the multi-agent orchestration layer (using LangGraph, Semantic Kernel, or custom MAS frameworks) that coordinates autonomous security tasks across the enterprise. * Drive the ...

Design and implement the multi-agent orchestration layer (using LangGraph, Semantic Kernel, or custom MAS frameworks) that coordinates autonomous security tasks across the enterprise. * Drive the ...

Experience with LangChain, LangGraph, NVIDIA NIM, or Hugging Face * Experience leading AI or ERP transformation programs for large enterprises The wage range for this role takes into account the wide ...

Deployed Engineer (Austin)

Austin, TX · On-site

$150K - $250K/yr

Today, our platform includes LangSmith (Observability, Evaluation, Deployment, Fleet, and Sandboxes), our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched ...

LangChain, LangGraph, LlamaIndex, CrewAI, AutoGen, or related frameworks * RAG architectures and vector databases (Pinecone, Weaviate, Qdrant, Chroma, Milvus) * Experience with cloud platforms (AWS ...

Design and implement the multi-agent orchestration layer (using LangGraph, Semantic Kernel, or custom MAS frameworks) that coordinates autonomous security tasks across the enterprise. * Drive the ...

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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 Austin, TX?

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

What job categories do people searching Langgraph jobs in Austin, TX look for?

The top searched job categories for Langgraph jobs in Austin, TX are:

What cities near Austin, TX are hiring for Langgraph jobs?

Cities near Austin, TX with the most Langgraph job openings:

Infographic showing various Langgraph job openings in Austin, TX as of August 2026, with employment types broken down into 1% Internship, 90% Full Time, 3% Part Time, and 6% Contract. Highlights an 80% Physical, 5% Hybrid, and 15% Remote job distribution.

IT - Technology Architect | Big Data - NoSQL | Graph Databases

Spruce Infotech

Austin, TX • On-site

$63.25 - $81.25/hr

Full-time

Re-posted 24 days ago


Job description

Senior Agentic Platform architect (Contract)
Tower / Track: Data & Reporting
Role: Senior Agentic Platform architect
Location: Austin / SCV
Experience Required: 10+ Years
Role Overview: Senior Agentic Platform Engineer to act as the lead architect and hands-on contributor for the Intelligence Layer. The role focuses on building production-ready agentic AI systems, integrating multi-agent orchestration with enterprise knowledge graphs and trusted data platforms.
Key Responsibilities
• Design and implement multi-agent architectures using LangGraph, including stateful workflows and Human-in-the-Loop checkpoints.
• Develop ontology-to-schema pipelines mapping enterprise ontologies (OWL / SKOS) into TigerGraph.
• Build and optimise graph-based intelligence using TigerGraph and GSQL.
• Materialise trusted data products in Snowflake using dbt, including Data Quality and trust-score automation.
• Develop internal and external AI agents supporting Data Operations and governed insights.
• Support CI/CD pipelines and production deployment for agentic AI systems.
Key Skill Set (Filtering Criteria)
• Python (FastAPI, async programming) - Mandatory.
• Advanced SQL - Mandatory.
• LangGraph / LangChain for agent orchestration.
• TigerGraph and GSQL development.
• Snowflake and dbt (Data Quality, analytics engineering).
• Enterprise knowledge modelling (OWL / SKOS / RDF).
• Strong communication and ability to work independently.
Preferred (Nice to Have)
• Experience with vector databases or RAG architectures.
• Exposure to metadata management tools such as DataHub.
• Familiarity with B2B/B2C sales data and CRM systems (e.g., Salesforce).
• Knowledge of data governance and security frameworks.
Contractor Expectations
• Work autonomously with minimal supervision and deliver production-ready solutions.
• Act as a senior technical reference for the team.
• Focus on stability, scalability, observability, and long-term platform health.