
Bain & Company
Principal AI Engineering Manager
- Permanent
- Dubai, United Arab Emirates
- Experience 5 - 10 yrs
Job expiry date: 26/05/2026
Job overview
Date posted
11/04/2026
Location
Dubai, United Arab Emirates
Salary
AED 30,000 - 40,000 per month
Compensation
Job description
Principal AI Engineering Manager within the AI, Insights & Solutions team in the Technology & Engineering function responsible for leading strategy, architecture, development, and deployment of AI-driven and software engineering solutions for enterprise clients across industries. The role operates within a multidisciplinary environment including analytics, engineering, product management, and design teams to develop human-centric, data-driven solutions leveraging artificial intelligence and advanced analytics. Responsibilities include shaping client solutions by translating business problems into product visions, prioritized backlogs, and engineering roadmaps while leading end-to-end client solution development from strategy ideation through architecture, engineering execution, deployment, adoption, and change enablement. The role requires leading cross-functional teams of designers, engineers, data scientists, and consultants while guiding clients on architecture modernization, microservices, platform strategy, engineering operating models, security, CI/CD, and engineering best practices. The position involves building production-grade, enterprise-scale AI applications, designing APIs using FastAPI, Node.js/Express, Flask, Django, .NET Core, or Java Spring Boot, and implementing scalable distributed systems using cloud platforms including AWS, Azure, and GCP with infrastructure-as-code technologies such as Terraform, CloudFormation, and Bicep. The role requires hands-on expertise in containerization and orchestration using Docker and Kubernetes, modern AI/ML development including LLM APIs, prompt engineering, RAG pipelines, and agentic SDKs, as well as modern web technologies including React, Angular, Vue.js, TypeScript, HTML5, and CSS3. The position also includes defining engineering best practices across software lifecycle phases including automated testing, performance profiling, CI/CD, observability, and resilient system design. The Principal AI Engineering Manager is responsible for coaching engineers across frontend, backend, platform, DevOps, and AI disciplines, leading recruitment and onboarding, acting as professional development advisor, and collaborating with senior leadership to drive talent development and transformation initiatives while supporting regional travel for client engagements.
Required skills
Key responsibilities
- Lead strategy, architecture, development, and deployment of AI-driven and software engineering solutions by translating business problems into product visions, engineering roadmaps, and scalable technical solutions
- Shape and scope client solutions by partnering with consulting teams, product owners, and stakeholders while managing cross-functional squads across engineering, data science, and design
- Lead end-to-end client solution development including business problem framing, strategy ideation, architecture design, engineering execution, deployment, adoption, and change enablement
- Deliver scalable, resilient, and high-quality software systems while ensuring technical delivery aligns with business strategy, operating model evolution, and measurable business impact
- Guide cross-functional teams on architecture modernization, microservices, platform strategy, engineering operating models, security, and software engineering best practices
- Define and implement engineering best practices across the full software lifecycle including CI/CD, automated testing, performance optimization, observability, and resilient system design
- Develop reusable software components, libraries, APIs, and enterprise-scale AI applications to accelerate delivery and improve platform reuse
- Coach and mentor engineering teams across frontend, backend, platform, DevOps, and AI while leading recruitment, onboarding, and professional development initiatives
Experience & skills
- Hold Master’s degree in Computer Science, Engineering, or related technical field with strong software engineering fundamentals including data structures, algorithms, and design patterns
- Possess 8+ years of hands-on experience in software development including version control, infrastructure, deployment, integration testing, and unit testing
- Demonstrate 3+ years of experience leading and managing software engineers across cross-functional engineering teams
- Exhibit experience building production-grade enterprise-scale AI applications, analytics platforms, and data-driven solutions
- Maintain expert knowledge of Python, JavaScript, and additional programming languages with experience building APIs using FastAPI, Node.js, Flask, Django, .NET Core, or Java Spring Boot
- Demonstrate experience with cloud platforms AWS, Azure, GCP and infrastructure-as-code technologies including Terraform, CloudFormation, or Bicep
- Show hands-on experience with Docker, Kubernetes, containerization, platform engineering, CI/CD pipelines, and cloud-native architecture design
- Exhibit experience with AI/ML technologies including LLM APIs, prompt engineering, RAG pipelines, agentic SDKs, and AI safety with Agile methodologies including Scrum, Kanban, and Git-based workflows