AI-Native Backend Engineer

Distyl; New York, San Francisco (NY, CA); Hybrid; USD 150,000 - 250,000; Full time

Benefits offered by this job

Equity

Medical insurance

Dental & Vision

Hybrid work model

Commuter benefits

401(k)

Job summary

Distyl is seeking a Backend & Systems Engineer to design, build, and optimize its AI‑native platform, Distillery, powering enterprise workflows. You will craft scalable backend services, focusing on reliability, security, and observability across cloud and on‑prem environments.

The role requires hands‑on work with Python, Kubernetes, and cloud platforms (AWS, GCP, Azure), plus collaboration with engineers and business leaders on real‑world AI deployment challenges.

Qualifications

• Proficiency in Backend & Systems Engineering.
• Experience building scalable, high‑performance backend services.
• Hands‑on experience with Kubernetes, CI/CD, and cloud platforms (AWS, GCP, Azure).
• Interest in AI‑native development and real‑world deployments.

Responsibilities

• Build & scale AI‑Native infrastructure for enterprise workflows.
• Develop cloud‑native microservices using Python, FastAPI, SQLAlchemy, Alembic.
• Ensure system reliability, security, and observability across AI workflows.
• Collaborate with cross‑functional teams to translate business needs into platform capabilities.

Skills

Backend & Systems

Python

Java

Golang

C++

Kubernetes

CI/CD

AWS

GCP

Azure

Infrastructure as Code

AI-native development

Security

Distributed systems

Observability

Tools

Kubernetes

CI/CD

AWS

GCP

Azure

Infrastructure as Code

Job description

Distyl is seeking a Backend & Systems Engineer to design, build, and optimize its AI‑native platform, Distillery, powering enterprise workflows. You will craft scalable backend services, focusing on reliability, security, and observability across cloud and on‑prem environments.

The role requires hands‑on work with Python, Kubernetes, and cloud platforms (AWS, GCP, Azure), plus collaboration with engineers and business leaders on real‑world AI deployment challenges.