Senior Backend Engineer - Enterprise AI Platform

NTT DATA AIVista; San Francisco (CA); Hybrid; USD 190,000 - 250,000; Full time

Benefits offered by this job

Medical, dental, and vision insurance

401(k) plan

Significant company HSA contribution

Paid holidays and flexible PTO

And other benefits

Job summary

NTT DATA AIVista, Inc. in Palo Alto, CA is hiring a Member of Technical Staff - Enterprise Engineering. Hybrid work supports building scalable backend services and integrating with enterprise systems to run agentic AI at scale.

You will own meaningful parts of the platform, write production-grade code, and collaborate with product, AI, and customer teams in a fast-moving, early-stage environment.

Qualifications

• 5+ years building and shipping production software.
• Bachelor's degree in a technical field or equivalent.
• Production-quality software engineering in Python and other modern languages (Go, TypeScript, Rust, or similar).
• Experience designing and building scalable backend services, APIs, and data systems.
• Hands-on experience deploying on AWS, Azure or GCP with containers/orchestration (Docker, Kubernetes, Helm).
• Comfortable working with LLM/AI systems; strong ownership and collaboration.

Responsibilities

• Build production services - design and ship scalable backend services and APIs.
• Integrate with the enterprise - data pipelines and integrations for real customer systems.
• Build the infrastructure to run agentic workflows in production.
• Own quality - write well-tested, maintainable code and raise engineering standards.
• Collaborate and iterate - work with product, AI, and customer teams; act on feedback.

Skills

Python

APIs

Backend design

Cloud deployment

LLM/AI integration

Ownership

Communication

Education

Bachelor's degree in a technical field

Tools

Docker

Kubernetes

Helm

Job description

NTT DATA AIVista, Inc. in Palo Alto, CA is hiring a Member of Technical Staff - Enterprise Engineering. Hybrid work supports building scalable backend services and integrating with enterprise systems to run agentic AI at scale.

You will own meaningful parts of the platform, write production-grade code, and collaborate with product, AI, and customer teams in a fast-moving, early-stage environment.