Senior Deployment Engineer

Kingston Stanley; Dubai; On-site; AED 350,000 - 520,000; Full time

Job summary

Kingston Stanley is seeking an experienced Deployment Engineering Manager in Dubai to lead the end-to-end deployment of AI-powered enterprise software. You will oversee design, implementation, and optimization of deployments across AWS, Azure, GCP, on-premise, and hybrid environments, ensuring security and production readiness.

You will work closely with the Founder and core engineering team, own timelines and budgets, and initially hands-on deploy, with the opportunity to scale a dedicated

Qualifications

• 7+ years of experience in deployment engineering, implementation, solutions engineering or technical delivery.

Responsibilities

• Lead end-to-end deployment of AI and enterprise software solutions from discovery to go-live and production support.

Skills

AI deployment

LLMs

RAG pipelines

Cloud deployment

Security & compliance

Leadership

Project management

Stakeholder management

Education

Bachelor's degree in Computer Science or Engineering

Tools

GPU infrastructure

Job description

We are seeking a Deployment Engineering Manager to lead the journey of AI-powered products from proof of concept to secure, production-ready deployment for enterprise clients.

This is a hands-on leadership role for someone experienced in deploying AI applications, LLM-based solutions, RAG pipelines and agentic AI systems across cloud, on-premise and hybrid environments.

Working directly with the Founder and alongside the core engineering team, you will own end-to-end deployment delivery, client integrations, production stability, security and technical implementation. You will initially lead deployments hands-on, with the opportunity to build and scale a dedicated deployment engineering team as the business grows.

Key Responsibilities

• Lead end-to-end deployment of AI and enterprise software solutions, from technical discovery to go-live and production support.
• Design and manage deployments across AWS, Azure, GCP, on-premise and hybrid environments.
• Oversee system integrations, APIs, infrastructure configuration, model serving and AI inference optimisation.
• Ensure deployments meet security, data protection and compliance requirements, including ISO 27001, SOC 2, GDPR and the EU AI Act, where applicable.
• Own deployment timelines, budgets, effort estimation, risk management and delivery quality.
• Develop deployment playbooks, SOPs and technical documentation to standardise implementation across clients.
• Collaborate with Engineering, Product, Sales and client stakeholders on technical scoping, integrations and production readiness.
• Ensure reliable production operations, smooth handovers and continuous improvement.
• Build and lead a deployment engineering team as the client base expands.

Requirements

• 7+ years of experience in deployment engineering, implementation, solutions engineering or technical delivery.
• Proven experience deploying AI applications into production, particularly LLMs, RAG pipelines and agentic AI systems.
• Hands-on experience with secure AI model deployment, GPU infrastructure, model serving and inference optimisation.
• Strong knowledge of cloud platforms (AWS, Azure or GCP), APIs, networking, system integration and infrastructure configuration.
• Experience managing complex, client-facing enterprise software deployments across multiple environments.
• Understanding of security, privacy and compliance frameworks, including ISO 27001, SOC 2, GDPR or the EU AI Act.
• Proven ability to lead technical teams or cross-functional workstreams.
• Strong project management, documentation, stakeholder management and problem-solving skills.
• Bachelor's degree in Computer Science, Engineering or a related field, or equivalent practical experience.

Ideal Candidate:

A hands-on technical leader who combines deep deployment expertise with AI production experience, commercial awareness and the ability to build scalable implementation processes in a growing technology business.