Python Backend Engineer in Dallas: AI Tooling & APIs

MACHINE LEARNING TECHNOLOGIES LLC; Dallas (TX); On-site; USD 83,000 - 152,000; Full time

Job summary

MACHINE LEARNING TECHNOLOGIES LLC in Dallas, TX is seeking a Backend Engineer - Python to design and implement scalable AI-oriented backends. You will develop APIs, data pipelines, and agent tooling used by AI agents.

The role requires 8+ years Python experience, FastAPI, Pydantic, Asyncio, and hands-on work with LangChain or LlamaIndex, PostgreSQL, and vector databases. Familiarity with Docker, Kubernetes, and cloud platforms is essential.

Qualifications

• 8+ years of professional Python experience with FastAPI, Pydantic, and Asyncio.
• Hands-on experience with LangChain or LlamaIndex.
• Proficiency in PostgreSQL and vector databases.
• Experience deploying containerized apps with Docker and Kubernetes on cloud providers.

Responsibilities

• Agent Logic & Tooling: Develop and maintain the backend 'tools' (APIs, scrapers, database connectors) used by AI agents.
• Orchestration Implementation: Use LangChain, LangGraph, or CrewAI to implement complex reasoning chains and multi-agent coordination.
• RAG Pipeline Engineering: Build and optimize data ingestion and retrieval systems using Vector Databases.
• Asynchronous Task Management: Manage long-running AI reasoning cycles with FastAPI/Asyncio and queues (Celery/Redis).
• API Architecture: Design secure REST or GraphQL APIs connecting backend to frontend.
• Safety & Guardrails: Implement backend-level validation to keep autonomous agent actions within secure boundaries.

Skills

Python

FastAPI

Asyncio

Pydantic

Git

CI/CD

Distributed systems

API design

Tools

LangChain

LlamaIndex

PostgreSQL

Vector databases

Docker

Kubernetes

AWS

Azure

GCP

Job description

MACHINE LEARNING TECHNOLOGIES LLC in Dallas, TX is seeking a Backend Engineer - Python to design and implement scalable AI-oriented backends. You will develop APIs, data pipelines, and agent tooling used by AI agents.

The role requires 8+ years Python experience, FastAPI, Pydantic, Asyncio, and hands-on work with LangChain or LlamaIndex, PostgreSQL, and vector databases. Familiarity with Docker, Kubernetes, and cloud platforms is essential.