Integration Engineer: Full stack Python (AI Agents, LangGraph, Context Engineering)

Overview

On Site
Depends on Experience
Contract - Independent
Contract - W2

Skills

Fullstack Development:Design
develop
and maintain end to end Python applications that interface with AI agents and backend services
ensuring robust
scalable
and maintainable codebases.
AI Agent Integration:Implement and orchestrate autonomous and semi-autonomous AI agents
connecting them with APIs
data sources
and user facing interfaces.
LangGraph Utilization:Leverage the LangGraph framework to construct
visualize
and manage complex conversational flows and agent interactions.
Context Engineering:Architect and implement systems for dynamic context management
memory
and prompt engineering to optimize agent behavior and user experience.
ystem Integration:Integrate machine learning models
vector databases
and third-party services
ensuring seamless interoperability across components.

Job Details

ole: Integration Engineer: Full stack Python (AI Agents, LangGraph, Context Engineering)

Location: 1st Atlanta, 2nd Dallas, 3rd Seattle (Onsite no remote)

Tax terms: C2C & W2

 

Visa: Any Visa expect OPT and CPT

 

Interview Process:

 1st Round Video interview 

 2nd Round In-Person interview 

Final Client Round In person interview  

 

Position Overview: We are seeking a talented and driven Integration Engineer with a strong fullstack Python background to join our AI solutions team. In this role, you will be responsible for building, integrating, and optimizing intelligent systems leveraging AI agents, the LangGraph framework, and advanced context engineering techniques. You will work across the stack, collaborating with data scientists, ML engineers, and product teams to deliver scalable, adaptive, and context aware solutions.

 

Key Responsibilities:

  • Fullstack Development: Design, develop, and maintain end to end Python applications that interface with AI agents and backend services, ensuring robust, scalable, and maintainable codebases.
  • AI Agent Integration: Implement and orchestrate autonomous and semi-autonomous AI agents, connecting them with APIs, data sources, and user facing interfaces.
  • LangGraph Utilization: Leverage the LangGraph framework to construct, visualize, and manage complex conversational flows and agent interactions.
  • Context Engineering: Architect and implement systems for dynamic context management, memory, and prompt engineering to optimize agent behavior and user experience.
  • System Integration: Integrate machine learning models, vector databases, and third-party services, ensuring seamless interoperability across components.
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About Nanda Technologies