AI Delivery Lead: Scrum Master for Production ML

Inception42

Abu Dhabi Emirate

On-site

AED 331,000 - 477,000

Full time

14 days+

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Job summary

Inception42, a G42 company, seeks an experienced Agile Delivery Lead to own day-to-day Agile execution for AI product and engineering teams. You will coordinate with Product, Engineering, Applied Science, Data, and Delivery to translate evolving inputs into visible, manageable work.

This role requires balancing experimentation with credible commitments and production-ready results. The ideal candidate has 6–10 years in Scrum/Agile, strong Jira discipline, and proven ability to forecast both

Qualifications

6–10 years of experience in Scrum, Agile delivery, or technical program execution within software-product, AI, SaaS, platform, or engineering organizations.

Responsibilities

Run sprint planning, daily coordination, reviews, retrospectives, refinement, and release-readiness activities with clear outcomes and disciplined follow-through.
Keep the backlog execution-ready by working with Product, Engineering, Applied Science, and Data owners to clarify intent, acceptance evidence, dependencies, and sequencing.
Structure AI experimentation as visible delivery work, including hypotheses, datasets, evaluation criteria, timeboxes, decision points, and paths to productionization.
Distinguish exploratory work from committed engineering delivery and help teams forecast both honestly without hiding uncertainty or abandoning accountability.
Track dependencies across data access and quality, model development, evaluation, infrastructure, security, integration, and deployment.
Remove impediments directly where possible and drive timely escalation when decisions, access, capacity, or external teams block progress.
Partner with technical leads to manage changing requirements and research findings while protecting sprint goals and making trade-offs explicit.
Use delivery metrics such as cycle time, throughput, blocked time, predictability, defect trends, and experiment outcomes to improve team performance.
Maintain accurate delivery information in Jira and related tools, ensuring boards, milestones, risks, and status views reflect reality.
Facilitate productive technical and product discussions, challenge unclear ownership, and keep decisions documented and actionable.
Strengthen team autonomy, continuous improvement, and delivery discipline across the full path from experiment to deployed product capability.