GenAI Backend Engineer | Python, GCP, RAG & Vector AI

MathCo; Bentonville (AR); On-site; USD 110,000 - 180,000; Full time

Job summary

MathCo is hiring a GenAI / Backend Software Engineer to build and scale production-ready Generative AI applications. You will blend strong software engineering with AI capabilities to deliver robust, scalable backend services.

You will work across backend APIs, cloud platforms (GCP), data pipelines, and RAG workflows, applying Git, CI/CD, testing, and production-quality practices to ship reliable solutions.

Qualifications

• 4+ years of software engineering experience.
• Strong programming experience with Python.
• Hands-on experience with Google Cloud Platform (GCP).
• Experience designing and developing backend services and APIs.
• Practical experience with LLM and Generative AI integrations.
• Understanding of RAG architectures, vector search, and vector databases.
• Experience with SQL and data ingestion.
• Familiarity with Git and CI/CD practices.

Responsibilities

• Design, develop, and enhance backend services and APIs using Python.
• Build and integrate LLM and Generative AI capabilities into applications.
• Develop and support Retrieval-Augmented Generation (RAG) pipelines.
• Work with vector search and vector databases to enable intelligent retrieval.
• Build and support SQL and data ingestion workflows.
• Apply strong engineering practices across Git, CI/CD, testing, and production-quality development.
• Collaborate with cross-functional teams to build reliable, scalable GenAI applications.

Skills

Python

GCP

LLM integration

RAG pipelines

Vector databases

SQL

Backend APIs

Git

CI/CD

Testing

Tools

Git

CI/CD

Testing

Job description

MathCo is hiring a GenAI / Backend Software Engineer to build and scale production-ready Generative AI applications. You will blend strong software engineering with AI capabilities to deliver robust, scalable backend services.

You will work across backend APIs, cloud platforms (GCP), data pipelines, and RAG workflows, applying Git, CI/CD, testing, and production-quality practices to ship reliable solutions.