Description

What sets me apart:

Lateral systems thinking, Computational thinking with experience in producing clear traceability from user needs, raw data to decisions, and the ability to design core product algorithms where none exist. Typical deliverables include discovery workshops, problem framing, product specs, working MVPs, decision-grade safety cases, and go-to-market-ready feature sets.

I help organisations ship reliable, AI-enabled products fast. As a Software Product Owner with experience across academia–industry collaborations and regulated domains, I turn fuzzy goals into audited, working systems. Recently, I owned the end-to-end vision for the Institutional Compass, supporting a George Washington University professor, and converted a scholarly method into a six-stage, LLM-driven workflow. I defined roadmaps, acceptance criteria, and managed backlogs; ran sprints across engineering and science students; architected versioned APIs and data models; and led QA from requirements through unit tests and pilots.

My background in safety-critical autonomy (University of Southampton & Thales) means I build with assurance in mind: AMLAS/SACE safety cases, V-model/V&V, Black Swan risk analysis, and standards such as ISO/IEC/IEEE 15026-4 and 15288. When teams need extra hands, I code in Python (accelerated by GitHub Copilot) for prototypes, data checks, and automation.

Industry field of expertise

Languages

English
Native or bilingual
Arabic
Native or bilingual

Workplace preferences

Remote only

Primarily works remotely

George Washington University
AI-Product Owner
CONSULTING AND AUDITS
June 2025 - Today (1 year)
Nottingham, United Kingdom
AI Product Owner, Institutional Compass:

- Owned the end-to-end vision that turned Professor Michelle Friend's book into an AI-enabled process. Converted the method into a six-stage, schema-driven workflow that nontechnical users can run and experts can audit.

- Set roadmap, acceptance criteria; ran backlog, and sprint reviews across coding and science teams.

- Architected the system: FastAPI backend, generic stage API, and static HTML/CSS/JS UI.

- Designed versioned JSON schemas to avoid hard-coded answers and to enable dynamic fields, Save, and Submit across Stage 1-6.

- Specified the data model for sessions, payloads, and results with reliable persistence and resume at any time.

- Created a brand new core algorithms: Compass sector mapping, objective degree heuristics, and final-arrow aggregation. Those are key concepts in the institutional compass theory which I had to learn and develop from scratch as there is no algorithm available online.

- Led quality assurance: system requirements, design, user stories, unit tests.

- Managed stakeholders and pilots; captured feedback, prioritised features, and trained users on method and tool.

Result: a near production-ready Institutional Compass (the project still ongoing) that links scholarship to execution, shortens analysis lead time, and provides traceable decisions from raw data to final compass and report.
Product management artificial intelligence product capability development and safety assurance Process Engineering AI and Software Capability Development
University of Southampton & Thales Group
Researcher – Safety‑Critical Autonomous‑Systems Solutions Engineering
EDUCATION AND E-LEARNING
September 2020 - June 2025 (4 years and 9 months)
Southampton, United Kingdom
- Led product solution conceptualisation & solution architecture for safety‑critical autonomy; captured customer needs, defined options, and validated methods to agreed satisfaction criteria. - Built AI Safety Cases using AMLAS and SACE patterns; demonstrated how training/testing datasets capture safety & systems requirements; argued for safety properties in unforeseeable scenarios.
- Drove requirements engineering: elicited and formalised complex requirements with traceability to tests and validation.
- Developed approaches for Black Swan failure discovery and mitigation in open, complicated environments. - Advanced the left‑side of the V‑model; created Vis&V methodology as an extension to traditional V&V for perception datasets.
- Reviewed and applied standards: ISO/IEC/IEEE 15026‑4:2021(e), ISO/IEC/IEEE 15288, PAS 1883:2020, INCOSE SE Handbook.
- Python engineering: authored scripts/tools to accelerate experiments, data checks, and evidence generation.
- Orchestrated collaboration & communication across University-Thales teams; presented at international workshops/conferences; tailored outputs for client audiences.
Product management product capability development and safety assurance Research and Development AI and Software Capability Development Systems Thinking
Synoptix
Project Engineer (Railways Systems Engineering)
CONSULTING AND AUDITS
December 2017 - July 2020 (2 years and 7 months)
Bristol, United Kingdom
Supported Bombardier functional architecture & requirements using IBM Rational DOORS and Jira.
- Authored Aventra trains V&V test plans and procedures; consolidated rail standards into system‑level test scripts.
- Executed FMEA QA/closure; managed I‑forms across Crossrail, London Overground, East Anglia, Southwest Trains, West Midlands Trains; produced KPIs and progress reports.
- Delivered mechanical part designs to mitigate water ingress on door controllers.
- Managed consultancy work packages: scoped deliverables, negotiated terms, and secured acceptance.
Product management Product Development Standards Compliance Process Engineering