Sr GenAI Engineer - Dallas, TX (Hybrid to work from office 3 days a week) and in-person interview mandatory. Must have strong experience in GenAI, NLP, LLM, Agentic AI, Prompt Engineer, LangChain, LangGraph, Google ADK(good to have). Should we very well versed in deployment process too.

  • Dallas, TX
  • Posted 1 day ago | Updated 1 day ago

Overview

On Site
Depends on Experience
Accepts corp to corp applications
Contract - W2
Contract - Independent

Skills

Artificial Intelligence
Collaboration
Database
Debugging
Decision-making
Generative Artificial Intelligence (AI)
LangChain
Management
Mentorship
Natural Language Processing
Orchestration
Python
Scalability
Software Engineering
Visualization
Workflow

Job Details

Job Title: Sr GenAI Engineer Location: Dallas, TX

Required Skills: GenAI, NLP, LLM, Agentic AI, Prompt Engineer, LangChain, LangGraph, Google ADK(good to have). Should we very well versed in deployment process too.
Job Summary:
We are looking for a highly experienced and technically elite Senior LangGraph Developer to architect and implement cutting-edge agentic workflows using LangGraph. This role demands deep expertise in building stateful, multi-agent systems that leverage LLMs for complex decision-making, orchestration, and automation. You will be responsible for designing resilient, scalable LangGraph architectures that power intelligent applications across domains.
Key Responsibilities:
Design and implement advanced LangGraph workflows with complex node logic, branching, and memory management.
Lead the development of agentic systems that interact, reason, and adapt dynamically.
Optimize performance and scalability of LangGraph graphs in production environments.
Integrate LangGraph with external APIs, databases, and LLMs to create seamless, intelligent pipelines.
Mentor junior developers and establish best practices for LangGraph development.
Collaborate with AI researchers and product teams to translate abstract ideas into robust LangGraph implementations.
Required Skills & Experience:
8+ years in software engineering, with at least 3-4 years in LangGraph or agentic frameworks.
Expert-level proficiency in Python, asynchronous programming, and graph-based computation.
Deep understanding of LLM orchestration, memory management, and stateful agent design.
Experience with LangChain, OpenAI, Anthropic, or similar LLM platforms.
Strong grasp of workflow debugging, graph visualization, and LangGraph Studio.
Proven ability to build production-grade agentic systems with high reliability and fault tolerance.

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