Backend AI Engineer — Unlimited PTO & Visa Sponsorship

voltai-com; Edison (CA); On-site; USD 140,000 - 210,000; Full time

Benefits offered by this job

Unlimited PTO

Comprehensive Health Coverage

Free Meals and Snacks

Professional Growth

Visa Sponsorship

Job summary

Voltai in the United States is seeking an experienced backend/data systems engineer to build scalable AI-driven tools for semiconductor design and data pipelines.

You will work across Windows, macOS, and web environments, integrate with LLM APIs, and collaborate with ML engineers to deliver production-grade systems.

The role requires strong Python and systems skills, plus Docker/Kubernetes, AWS, and secure, cost-efficient design.

Qualifications

• Proven experience building scalable backend and data systems.
• Strong Python programming and systems design skills.
• Experience with Unix-based environments and Bash scripting.

Responsibilities

• Build and maintain scalable backend systems powering AI-driven tools.
• Construct and manage large-scale data pipelines for diverse datasets.
• Assist with data extraction, cleaning, and QA across structured and unstructured formats.
• Develop and deploy agentic AI applications using LLM APIs.
• Integrate AI capabilities into cross-platform software products (Windows, macOS, web).
• Collaborate with ML engineers to serve models efficiently and securely.

Skills

Python

C/C++

Unix-based systems

Bash scripting

FastAPI/Django

AWS (ECS, Lambda, S3, EC2)

Databases (SQL/NoSQL)

Airflow/Prefect

Docker/Kubernetes

CI/CD (GitHub Actions, Argo CD)

AI/ML production systems

System design

Security best practices

Tools

Docker

Kubernetes

CI/CD tools

GitHub Actions

Argo CD

AWS

Airflow

Prefect

FastAPI

Django

Job description

Voltai in the United States is seeking an experienced backend/data systems engineer to build scalable AI-driven tools for semiconductor design and data pipelines.

You will work across Windows, macOS, and web environments, integrate with LLM APIs, and collaborate with ML engineers to deliver production-grade systems.

The role requires strong Python and systems skills, plus Docker/Kubernetes, AWS, and secure, cost-efficient design.