Senior Backend Engineer | AI Infrastructure & Distributed Systems

The Cypress Group; New York (NY); On-site; USD 160,000 - 240,000; Full time

Job summary

Confidential, venture-backed AI startup in New York City is seeking a senior backend engineer to design and own scalable infrastructure. You will work on distributed services, data pipelines, and AI-enabled workflows with significant technical ownership from the outset.

The role emphasizes building reliable APIs, expanding production capabilities, and shaping architectural decisions in partnership with engineering leadership.

Qualifications

• 5+ years of professional software engineering experience.
• Strong production experience with Go or Python.
• Experience designing and operating distributed backend systems.
• Solid understanding of databases, APIs, and cloud infrastructure.
• Experience building reliable, scalable production services.
• Ability to independently own complex technical projects.

Responsibilities

• Design and build scalable backend services using Go and/or Python.
• Develop infrastructure supporting AI-powered applications and intelligent workflows.
• Build reliable APIs, distributed systems, and data-processing pipelines.
• Design systems that can handle complex data and increasing production workloads.
• Improve performance, reliability, observability, and scalability.
• Work with engineering leadership to define technical architecture and infrastructure strategy.
• Help establish best practices for deployment, testing, and production operations.

Skills

Go

Python

Distributed systems

APIs

Cloud infrastructure

Production services

Tools

Kubernetes

Job description

Location: New York City

Compensation: $160,000–$240,000 base + equity

Company: Confidential, venture-backed AI startup

The Opportunity

What if you could help design the infrastructure behind an AI platform before the architecture is set in stone?

We're working with a venture-backed NYC startup building an enterprise AI platform, and they're looking for a senior engineer who wants to tackle challenging backend and infrastructure problems.

This is an opportunity to work on the systems that power intelligent applications at scale, from distributed services and data pipelines to the infrastructure supporting production AI.

You'll have significant technical ownership and the ability to influence architectural decisions from the beginning.

What You'll Work On

• Design and build scalable backend services using Go and/or Python.
• Develop infrastructure supporting AI-powered applications and intelligent workflows.
• Build reliable APIs, distributed systems, and data-processing pipelines.
• Design systems that can handle complex data and increasing production workloads.
• Improve performance, reliability, observability, and scalability.
• Work with engineering leadership to define technical architecture and infrastructure strategy.
• Help establish best practices for deployment, testing, and production operations.

What We're Looking For

• 5+ years of professional software engineering experience.
• Strong production experience with Go or Python.
• Experience designing and operating distributed backend systems.
• Solid understanding of databases, APIs, and cloud infrastructure.
• Experience building reliable, scalable production services.
• Ability to independently own complex technical projects.
• Strong engineering fundamentals and a pragmatic approach to problem-solving.

Especially Interesting Backgrounds

• Engineers from developer infrastructure or cloud-native startups.
• Backend engineers who have built data-intensive applications.
• Engineers with experience in distributed systems, Kubernetes, or event-driven architectures.
• Engineers who have helped scale an early-stage company's infrastructure.
• Engineers who have worked on AI platforms, LLM infrastructure, or agentic systems.

Why This Opportunity?

• Influence the architecture of a growing AI platform.
• Work on technically challenging problems with real-world applications.
• Join a small team where your engineering decisions matter.
• Build systems from the ground up rather than maintain legacy infrastructure.
• Competitive compensation, meaningful equity, and long-term growth potential.

Interested in building the infrastructure behind the next generation of AI applications?