- MBA candidate and former Senior Cloud & ML Engineer with 6+ years building AI and data products across enterprise SaaS, IoT, and network analytics, now focused on LLM-powered workflows and AI product strategy.
- Design…
- MBA candidate and former Senior Cloud & ML Engineer with 6+ years building AI and data products across enterprise SaaS, IoT, and network analytics, now focused on LLM-powered workflows and AI product strategy.
- Designed and shipped generative AI and agentic workflows using prompt engineering, tool-bounded LLMs, and experimentation frameworks to translate complex technical capabilities into clear business requirements, user stories, and roadmaps.
- Hands-on experience with secure, compliant AI in regulated, enterprise contexts, improving test coverage, traceability, and risk-aware rollout for data- and AI-powered features while coordinating with cross-functional engineering, product, and stakeholder teams.
- Strong analytical and communication skills demonstrated through quantified impact (cost, reliability, cycle time), thought leadership on data governance, and mentoring engineers on responsible GenAI use and experimentation best practices.
● Designed and prototyped LLM-powered AI workflows for consumer and enterprise use cases, using prompt engineering, tool-routing rules, and evaluation rubrics to rapidly iterate and validate features aligned with business requirements and user stories.● Developed interactive prototypes and visualised user journeys with Whimsical and personas via UXPressia, enabling data-informedprioritisation of features and early testing with stakeholders.● Applied AI experimentation frameworks with explicit success criteria, failure modes, and guardrails to assess the feasibility ofgenerative AI and AI agent automations, reducing consultation and feature validation cycles by 70% and informing compliant, risk-aware rollout decisions.● Translated early LLM and automation experiments into a roadmap for product adoption, aligning AI capabilities with business anduser needs, and prioritising agentic use cases based on customer pain points and competitive insights.● Delivered insights from user testing and rapid experimentation that informed next-generation generative AI features, improvingearly-adopter engagement and demonstrating scalable AI product thinking across onboarding and policy-like workflows.
● Promoted to lead core React, Typescript, and AWS stack, refactoring AWS architecture and APIs to centralise monitoring, tightensecurity, and remove redundancies. Applied GenAI tool-routing to speed delivery while maintaining secure, compliant practices.● Mapped user journeys, implemented API security and monitoring best practices, and coordinated cross-functional teams; reducedambiguity through LLM/GenAI-assisted drafts for user stories and documentation, using clear constraints, context management,and acceptance criteria.● Designed release flows and integrated automated testing for services and UI, raising test coverage to 92% and improving platformreliability, using prompt-based test generation with LLMs and evaluation rubrics to expand coverage faster.● Led cross-business implementation and delivery of a multimillion-dollar Microsoft-partnered IoT platform by defining end-to-endingestion paths and guiding adoption. Cut cloud spend by 30% and reduced compute costs by 20%, aligning execution with productstrategy.● Built a hardware-aligned EV-charging simulator to remove integration bottlenecks, enabling one-touch deployments andaccelerating stakeholder validation, informing roadmap prioritisation.● Designed release flows and integrated automated testing for services and UI, raising test coverage to 92% and improving platformreliability for faster, higher-quality feature rollout.● Redesigned metadata pipelines with durable Azure Functions and surfaced lineage in Purview, reducing redundant operations by30% and improving downstream model traceability and auditability for data- and AI-powered features in a regulated, enterprisecontext.● Mentored junior engineers, setting best practices for cloud ML delivery, applied data science projects, and responsible use ofgenerative AI tools in production-like environments.
● Designed and validated a hybrid statistical forecasting system for optic failures, achieving 90%+ week-level accuracy and 6–8months lead time. This proactive insight informed maintenance strategy and influenced product roadmap prioritisation.● Developed ETL pipelines to improve analytics data availability, moving optics telemetry into Athena with SQL transformations.Improved data accessibility and processing efficiency by 20%, enabling faster, data-driven product decisions.● Standardised ML deployments with one-command CI/CD flows and automated checks, reducing deployment errors to near zeroand cutting setup time by 15%. This ensured reliable feature delivery for cross-functional stakeholders.● Prototyped an NLP-based anomaly detection scoring system using LSTM experiments, improving detection capability and providingactionable insights for security feature planning.
نظام التوظيف التشغيلي المعتمد على الذكاء الاصطناعي أولاً، الذي يوحّد ويؤتمت دورة التوظيف بالكامل للمؤسسات الحديثة حول العالم.
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