Engineering Manager

Norman Alex; Dubai; On-site; USD 120,000 - 180,000; Full time

Job summary

An innovative venture is seeking an Engineering Manager to spearhead AI application development. This role involves leading the design and deployment of AI-powered software products while establishing a robust engineering culture. As the first technical hire, you will have the autonomy to shape the architecture and infrastructure, ensuring high performance and scalability. Collaborate with stakeholders to translate strategic goals into functional applications, while mentoring future team members. If you are passionate about AI and eager to make a significant impact in a dynamic environment, this opportunity is perfect for you.

Qualifications

• 5-10 years of experience in full-stack or backend software development.
• Strong proficiency in Python and experience with AI platforms.

Responsibilities

• Lead the design and development of AI-centric applications.
• Set up cloud infrastructure and implement DevOps workflows.

Skills

Python

AI Application Development

TypeScript

JavaScript

Go

Cloud Services (AWS, GCP, Azure)

DevOps Practices

Microservices

APIs

Education

Bachelor's Degree in Computer Science

Master's Degree in Software Engineering

Tools

AWS

GCP

Azure

CI/CD Pipelines

Containerization

Job description

Role Overview

We are seeking a highly capable and entrepreneurial Engineering Manager to serve as the founding technical manager in a new AI-focused venture backed by a family office. As the first engineer on the ground, you will lead the design and development of AI-centric applications. You’ll own end-to-end delivery, from backend systems to user interfaces, with autonomy and a high degree of influence.

Key Responsibilities

1. AI Application Development

• Design, develop, and deploy AI-powered software products that integrate with foundation models (e.g., OpenAI, Anthropic) or other AI services via APIs and on-prem LLMs.
• Train and fine-tune AI models for downstream tasks.
• Translate product ideas and strategic objectives into functional, scalable, and user-friendly applications. Build backend services, orchestrate workflows, and develop front-end interfaces to create seamless end-user experiences.

Systems & Architecture Design

• Architect modular and extensible systems that support rapid experimentation and deployment of new AI features. Make critical decisions on frameworks, libraries, data structures, and cloud-native design patterns tailored to AI applications.
• Prioritize maintainability, reusability, and performance.

Infrastructure & Deployment for AI Use Cases

• Set up cloud infrastructure (e.g., AWS, GCP, or Azure) to host applications and manage secure, scalable data and API integrations.
• Implement lightweight DevOps workflows: CI/CD pipelines, containerization, and monitoring for deployed applications.
• Ensure infrastructure is optimized for latency, concurrency, scalability, and cost-efficiency of AI-powered systems.

Cross-Functional Collaboration

• Work directly with stakeholders and domain experts to define features and development priorities. Participate in product ideation and contribute to shaping the roadmap through technical insight. Provide clear, actionable technical feedback to non-technical decision-makers.

Engineering Culture & Best Practices

• Establish coding standards, version control workflows, code reviews, and testing protocols appropriate for a lean startup.
• Document systems and maintain a developer-friendly environment for future hires.
• Act as a mentor and technical reference point for future engineering team growth.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related technical discipline.
• 5-10 years of hands-on experience in full-stack or backend software development, ideally with exposure to AI-powered products.
• Strong proficiency in Python is essential; experience with TypeScript, JavaScript, or Go is a plus. Experience building applications that integrate with AI platforms (e.g., OpenAI, Anthropic, Google Vertex AI). Experience in building microservices, APIs, authentication/authorization flows, and backend orchestration. Proficient with cloud services, containerization, and basic DevOps practices.
• Proven track record of leading an engineering team to deliver AI applications and services.