AI / Python Architect

InfoVision Inc.; Dallas (TX); On-site; USD 140,000 - 190,000; Full time

Job summary

InfoVision Inc. is seeking an experienced AI / Python Architect to design scalable backend and AI services in a Dallas-based enterprise environment. The role focuses on agent-based workflows, LLM orchestration, and event-driven architectures using Claude and MCP.

You will build Python-based AI agents, integrate with vector databases, and deploy scalable microservices with Spring Boot and Spring Cloud. Strong mastery of Kafka and REST/gRPC APIs is required.

Qualifications

• Hands-on experience designing and deploying enterprise-grade AI solutions.
• Strong expertise with scalable microservices and event-driven architectures.
• Experience integrating LLMs into enterprise applications.

Responsibilities

• Architect and deploy scalable microservices using Spring Boot and Spring Cloud.
• Design and develop RESTful and gRPC APIs to support enterprise AI services.
• Develop Python-based AI agent services and AI-driven backend solutions.
• Orchestrate LLM-powered applications using LangChain, LlamaIndex, AutoGen, LangGraph.
• Build MCP servers for AI agents to interact with tools and enterprise systems.
• Create AI agent skills and reusable agent capabilities.
• Design AI-driven workflows for enterprise use cases.
• Work with vector databases to support LLM retrieval capabilities.
• Apply prompt engineering to improve LLM performance and reliability.
• Architect event-driven systems and real-time streaming with Apache Kafka.

Skills

Architectural design

Cloud architecture

Microservices

AI/LLM engineering

Python programming

Prompt engineering

Education

Bachelor's degree in CS/Engineering

Tools

Spring Boot

Spring Cloud

REST APIs

gRPC

Apache Kafka

Claude

LangChain

LlamaIndex

AutoGen

LangGraph

Vector Databases

Job description

Position Overview

We are seeking an experienced AI / Python Architect with strong expertise in scalable microservices, Python-based AI agent services, LLM orchestration, and event-driven architectures. The ideal candidate will have hands-on experience designing and deploying enterprise-grade AI solutions using Claude, Model Context Protocol (MCP), agent-based workflows, vector databases, and Apache Kafka.

This role will be responsible for architecting scalable backend and AI services, developing intelligent agent workflows, and integrating LLM capabilities into enterprise applications.

Key Responsibilities

• Architect and deploy scalable microservices using Spring Boot and Spring Cloud.


• Design and develop robust RESTful and gRPC APIs to support enterprise applications and AI services.


• Design and develop Python-based AI agent services and AI-driven backend solutions.


• Develop and orchestrate LLM-powered applications using frameworks such as LangChain, LlamaIndex, AutoGen, and LangGraph.


• Design and implement LLM-powered solutions using Claude, including enterprise AI workflows and agent-based applications.


• Build and integrate Model Context Protocol (MCP) servers to enable AI agents to interact with tools, data, and enterprise systems.


• Create and implement AI agent skills and reusable agent capabilities.


• Design and develop AI-driven workflows for enterprise use cases.


• Work with vector databases to support LLM applications and intelligent retrieval capabilities.


• Apply advanced prompt engineering techniques to improve LLM performance and reliability.


• Architect and implement event-driven systems and real-time message streaming using Apache Kafka.


• Design Kafka-based solutions supporting scalable, reliable, and distributed enterprise applications.


• Collaborate with engineering and architecture teams to translate business requirements into scalable AI and backend solutions.

Required Technical Skills

AI / LLM

• Strong hands-on experience with LLMs, specifically Claude.


• Strong experience with LLM orchestration frameworks such as:


• LangChain


• AutoGen


• LangGraph


• Hands-on experience with AI agents and agentic workflows.


• Experience building MCP servers and working with the Model Context Protocol.


• Experience creating agent skills and AI-driven workflows.


• Deep knowledge of vector databases and their use in LLM applications.


• Extensive experience architecting and deploying scalable microservices.


• Strong experience with Spring Boot and Spring Cloud.


• Strong experience designing and developing RESTful APIs and gRPC services.


• Deep expertise in Apache Kafka.


• Strong understanding of event-driven architecture and message streaming.

Ideal Candidate

The ideal candidate combines strong software architecture skills with deep hands-on AI/LLM engineering experience. This is not purely an AI research or prompt-engineering role. Candidates should be capable of building production-grade services, integrating LLMs and agents into enterprise systems, and designing scalable event-driven architectures.

Key areas of expertise:

• Python | Claude | LLMs | AI Agents | MCP | LangChain | LangGraph | LlamaIndex | AutoGen | Vector Databases | Prompt Engineering | Spring Boot | Spring Cloud | REST | gRPC | Apache Kafka | Microservices