Python Backend Engineer for AI SaaS (FastAPI)

HireHi; United States; Remote; USD 120,000 - 170,000; Full time

Job summary

HireHi is seeking a skilled Backend Engineer to build production backend services with Python, FastAPI, and PostgreSQL. You will design scalable APIs, integrate LLM APIs, and deploy on AWS, using Docker and Redis to ensure performance. Collaborate with AI, Product, and Software teams to turn research into production features, while ensuring reliability and security in a fast-paced SaaS environment.

Qualifications

• 3+ years in backend/software/AI engineering.
• Strong Python development experience.
• Experience with FastAPI or similar Python backend frameworks.
• Experience with PostgreSQL.
• Knowledge of REST APIs and backend architecture.
• Experience with Docker.
• Experience with AWS.
• Experience with Redis.
• Experience integrating LLM APIs into production.

Responsibilities

• Build production backend services and APIs using Python and FastAPI.
• Integrate LLM APIs into customer-facing applications and workflows.
• Design scalable REST APIs and service architectures.
• Build data models and services using PostgreSQL.
• Use Redis for caching, queues, and application performance.
• Integrate AI services with internal and external APIs.
• Containerise applications and services using Docker.
• Deploy and operate backend workloads on AWS.
• Build asynchronous and background processing workflows.
• Improve API performance, reliability, and scalability.
• Implement authentication, logging, monitoring, and error handling.
• Collaborate with AI, Product, and Software Engineers to turn AI capabilities into production features.

Skills

Python

Backend

REST API

AWS

PostgreSQL

Redis

Docker

FastAPI

AI integration

Tools

Docker

AWS

Redis

PostgreSQL

FastAPI

Job description

HireHi is seeking a skilled Backend Engineer to build production backend services with Python, FastAPI, and PostgreSQL. You will design scalable APIs, integrate LLM APIs, and deploy on AWS, using Docker and Redis to ensure performance. Collaborate with AI, Product, and Software teams to turn research into production features, while ensuring reliability and security in a fast-paced SaaS environment.