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Home/Jobs in UAE/Technology Jobs/Director - Software Engineering
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Inception42

Director - Software Engineering

🇦🇪 Abu Dhabi, UAE🏢 On-site

💰 Estimated salary: AED 26,000–40,000/month· MenaJobs market estimate

Software EngineeringAIMLOpsDevSecOpsArchitectureData Infrastructure

At a Glance

Category
💻 Technology
Level
C-Level
Type
Full-time
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Inception42 logo
Inception42

Inception42, a G42 company, is the region’s leading innovator of AI-powered domain-specific as well as industry-agnostic products, built on a rich heritage of research and development. Within the G42 ecosystem, Inception functions as the core intelligence layer – transforming data and compute infrastructure into real-world, applied AI solutions. Beyond its commercial endeavors, Inception is committed to creating positive societal impact. For more information, please visit www.inception42.ai

Overview:

As Director - Software Engineering at Inception42, you will lead multidisciplinary engineering teams responsible for building and operating production AI products and platforms. You will set technical direction, strengthen engineering execution, and ensure that software, data, and machine learning systems are reliable, secure, and scalable. The role operates across product delivery, architecture, quality, DevSecOps, and applied R&D in a high-ownership environment focused on real-world deployment.

Responsibilities:

  • Set engineering direction and execution priorities in line with Inception42’s product, technology, and business objectives.
  • Lead, develop, and support engineering managers and senior technical leaders across multidisciplinary teams.
  • Build an engineering culture grounded in ownership, technical rigor, collaboration, and continuous improvement.
  • Drive planning and delivery across complex engineering initiatives, making clear trade-offs across scope, time, resourcing, cost, and quality.
  • Guide architecture and technical decisions across software platforms, data infrastructure, machine learning pipelines, and model deployment systems.
  • Improve the scalability, reliability, performance, and operability of production data and ML systems.Establish engineering standards for data management, MLOps, testing, release quality, observability, and operational readiness.
  • Embed security and compliance into the software development lifecycle through practical DevSecOps controls and automation.
  • Sponsor focused R&D initiatives, evaluate emerging technologies, and move credible experiments into production capabilities.
  • Collaborate closely with Product, Data, AI/ML, Security, and Enterprise Architecture to align technical execution with customer and business outcomes.
  • Create clear operating mechanisms for delivery health, technical risk, engineering quality, and team effectiveness.
  • Communicate engineering strategy, progress, trade-offs, and outcomes clearly to technical and executive stakeholders.

Qualifications:

• Strong engineering fundamentals and a demonstrated track record of leading diverse engineering teams
through complex delivery.
• Experience shipping and operating production software, data, or machine learning systems at meaningful
scale.
• Deep understanding of data infrastructure, MLOps, quality engineering, DevSecOps, and the software
development lifecycle.
• Ability to translate company objectives into technical strategy, operating plans, architecture priorities, and
measurable outcomes.
• Sound systems thinking and judgment across reliability, security, performance, cost, and delivery speed.
• Strong communication skills, with the ability to align technical teams and explain decisions to senior
stakeholders.
• Comfort operating in ambiguity, resolving competing priorities, and taking accountability for execution.
• Bachelor’s degree in Engineering, Computer Science, or equivalent practical experience.                                                             Nice to Have

• Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
• Experience with regulated, multi-tenant, high-availability, or national-scale platforms.
• Exposure to applied AI products, research collaborations, or production model-serving environments.
• Experience leading platform modernization, organizational scaling, or engineering operating-model changes.
Inception42 is building AI systems designed for practical deployment at scale — across industries,
infrastructure, and national-level initiatives.
If you want to work close to both advanced AI capability and real-world execution, we’d like to hear from
you.What We Look ForIf you are a performance-driven, inquisitive mind with the agility to adapt to ambiguity, you will fit right in. You should be eager to explore opportunities to build meaningful collaborations with stakeholders and aspire to create unique customer-centric solutions. Bias for action and a passion to conquer new frontiers in the AI space is at the heart of the Inception42 community.What Working At Inception42 OffersCulture: An open, diverse and inclusive environment with a global vision that encourages personal growth and focuses on ground-breaking, industry-first innovations.Career: Outstanding learning, development & growth opportunities via structured training programs and innovative, high-tech projects.Rewards: A competitive remuneration package with a host of perks including healthcare, education support, leave benefits and more.If you can confidently demonstrate that you meet the criteria above, please contact us as soon as possible.

Requirements

  • •Strong engineering fundamentals
  • •Demonstrated track record of leading diverse engineering teams through complex delivery
  • •Experience shipping and operating production software, data, or machine learning systems at meaningful scale
  • •Deep understanding of data infrastructure, MLOps, quality engineering, DevSecOps, and the software development lifecycle
  • •Ability to translate company objectives into technical strategy, operating plans, and architecture

Responsibilities

  • •Set engineering direction and execution priorities in line with product, technology, and business objectives
  • •Lead, develop, and support engineering managers and senior technical leaders
  • •Build an engineering culture grounded in ownership, technical rigor, collaboration, and continuous improvement
  • •Drive planning and delivery across complex engineering initiatives
  • •Guide architecture and technical decisions across software platforms, data infrastructure, ML pipelines, and model deployment systems
  • •Improve scalability, reliability, performance, and operability of production data and ML systems
  • •Establish engineering standards for data management, MLOps, testing, release quality, observability, and operational readiness
  • •Embed security and compliance into the software development lifecycle through DevSecOps controls

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