Senior Backend Engineer: Scalable AI APIs & Data Pipelines

NorthBay Solutions LLC; Abu Dhabi; On-site; AED 240,000 - 360,000; Full time

Job summary

NorthBay Solutions LLC is seeking a Senior Backend Engineer to architect and build scalable APIs and data processing pipelines powering AI-driven systems in Abu Dhabi. You will integrate ML models into production workflows, manage data orchestration, and ensure reliability and performance of AI services.

The role focuses on developing secure, high-performance backend services with REST/GraphQL, Docker/Kubernetes, and cloud platforms, while collaborating with ML and DevOps teams to deploy models

Qualifications

• 5+ years backend development experience.
• Proficiency in TypeScript, REST/GraphQL, PostgreSQL and MongoDB.
• Experience with event-driven architecture (Kafka, RabbitMQ) and cloud platforms (AWS, Azure).
• Familiarity with containerization using Docker and orchestration with Kubernetes.

Responsibilities

• Design and develop backend services with scalable REST and GraphQL APIs.
• Integrate ML inference endpoints, batch jobs, and model serving workflows.
• Collaborate with DevOps and ML engineers to deploy models and manage large datasets.
• Implement secure, high-performance backend systems with caching, queuing, and monitoring.
• Wrap models into APIs and deploy to production environments.
• Write reusable modules, implement unit/integration tests, and support CI/CD workflows.

Skills

5+ years backend

TypeScript

REST/GraphQL

PostgreSQL

MongoDB

Kafka

RabbitMQ

AWS

Azure

Docker

Kubernetes

FastAPI

Triton

TorchServe

Tools

Git

Job description

NorthBay Solutions LLC is seeking a Senior Backend Engineer to architect and build scalable APIs and data processing pipelines powering AI-driven systems in Abu Dhabi. You will integrate ML models into production workflows, manage data orchestration, and ensure reliability and performance of AI services.

The role focuses on developing secure, high-performance backend services with REST/GraphQL, Docker/Kubernetes, and cloud platforms, while collaborating with ML and DevOps teams to deploy models