Integration Engineer: Full stack Python (AI Agents, LangGraph, Context Engineering)
AceStack LLC
Role: Integration Engineer: Full stack Python (AI Agents, LangGraph, Context Engineering)
Location: Atlanta, Dallas, Seattle (Onsite no remote)
Positions: 5
Interview Process:
TechM 1st Round - Video interview with TechM
TechM 2nd Round - In-Person interview with TechM
Final Client Round - In person interview with AT&T
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:
Location: Atlanta, Dallas, Seattle (Onsite no remote)
Positions: 5
Interview Process:
TechM 1st Round - Video interview with TechM
TechM 2nd Round - In-Person interview with TechM
Final Client Round - In person interview with AT&T
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.
Vacancy posted 2 days ago
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