Senior Development Manager AI Products & Solutions

In this role, you'll lead an engineering team building AI-enabled products and platforms while driving strong execution, delivery predictability, and team growth. You'll own planning and delivery across the full development lifecycle: roadmap translation, scope management, staffing, prioritization, sprint execution, release planning, risk management, dependency handling, and stakeholder communication. On the technology side, you'll guide teams building scalable services, data pipelines, ML-enabled applications, and LLM-based features, ensuring sound engineering around architecture, quality, observability, security, and operational readiness. You ll help the team make good decisions about model integration, experimentation, evaluation, deployment, monitoring, and governance, while balancing innovation with business value, cost, and time to market. Your impact will be measured not just by delivery, but by the strength of the team, the quality of execution, and the adoption of AI capabilities that solve real customer problems.

What you bring

• You bring a strong software engineering foundation with the ability to lead teams building scalable products, services, platforms, and AI-enabled applications

• You have a working understanding of machine learning and generative AI concepts, including model lifecycle, LLM use cases, evaluation, deployment constraints, and production risks

• You are experienced in leading delivery of AI or data-intensive programs, aligning product scope, technical dependencies, staffing plans, and execution milestones

• You bring strong project and program management skills, including roadmap planning, estimation, sprint execution, release coordination, risk management, and dependency tracking

• You have experience managing engineers across diverse skill sets, including backend, frontend, data engineering, machine learning, and platform engineering

• You are skilled at establishing delivery metrics, engineering KPIs, and operational cadences that improve execution predictability and quality

• You have a strong understanding of agile methodologies, backlog management, prioritization, stakeholder communication, and escalation handling

• You bring practical knowledge of cloud platforms, DevOps, CI/CD, observability, security, and the operational needs of production AI systems

• You are able to evaluate technical trade-offs, including build vs. buy, delivery speed vs. technical debt, and experimentation vs. reliability

• You demonstrate strong people leadership skills, including hiring, coaching, performance management, and building high-performing teams

• You are confident working with senior stakeholders to translate business goals into execution plans, budgets, staffing decisions, and measurable outcomes

• You apply sound judgment around responsible AI, data governance, compliance, and quality standards in enterprise environments

• You bring 8-10(+) years of experience in software engineering, architecture, or a related field, with a strong track record of designing and delivering complex systems

• You are a strong people leader who is passionate about developing talent and building inclusive, high-performing teams

• You are proactive, organized, and outcomes-driven, with a strong sense of ownership and accountability

• You are a collaborative leader who builds strong partnerships across product, architecture, and business teams

• You have a commitment to responsible AI principles, including ethics, transparency, and governance

• Fluent professional English (written and spoken) is required; Arabic is a plus

• You bring a strong software engineering foundation with the ability to lead teams building scalable products, services, platforms, and AI-enabled applications

• You have a working understanding of machine learning and generative AI concepts, including model lifecycle, LLM use cases, evaluation, deployment constraints, and production risks

• You are experienced in leading delivery of AI or data-intensive programs, aligning product scope, technical dependencies, staffing plans, and execution milestones

• You bring strong project and program management skills, including roadmap planning, estimation, sprint execution, release coordination, risk management, and dependency tracking

• You have experience managing engineers across diverse skill sets, including backend, frontend, data engineering, machine learning, and platform engineering

• You are skilled at establishing delivery metrics, engineering KPIs, and operational cadences that improve execution predictability and quality

• You have a strong understanding of agile methodologies, backlog management, prioritization, stakeholder communication, and escalation handling

• You bring practical knowledge of cloud platforms, DevOps, CI/CD, observability, security, and the operational needs of production AI systems

• You are able to evaluate technical trade-offs, including build vs. buy, delivery speed vs. technical debt, and experimentation vs. reliability

• You demonstrate strong people leadership skills, including hiring, coaching, performance management, and building high-performing teams

• You are confident working with senior stakeholders to translate business goals into execution plans, budgets, staffing decisions, and measurable outcomes

• You apply sound judgment around responsible AI, data governance, compliance, and quality standards in enterprise environments

• You bring 8-10(+) years of experience in software engineering, architecture, or a related field, with a strong track record of designing and delivering complex systems

• You are a strong people leader who is passionate about developing talent and building inclusive, high-performing teams

• You are proactive, organized, and outcomes-driven, with a strong sense of ownership and accountability

• You are a collaborative leader who builds strong partnerships across product, architecture, and business teams

• You have a commitment to responsible AI principles, including ethics, transparency, and governance

• Fluent professional English (written and spoken) is required; Arabic is a plus