Senior Android Engineer, Building Toward AI Engineering
Android developer with 13+ years building scalable, high-performance mobile apps — now advancing into AI with IBM certifications, applying that thinking to app intelligence and user experience.
Profile
Senior Android Engineer, Building Toward AI Engineering
Android developer with 13+ years building scalable, high-performance mobile apps across fintech, e-commerce, and consumer products. Currently advancing in AI through IBM certifications in AI agents and agentic AI, applying that thinking to app intelligence and user experience.
01 — The Path
A single trunk of software and Android engineering — and the point where AI engineering splits off as a second, active track. Expand any stage for the detail.
Entry into software development — learned and worked across HTML, JavaScript, CSS, PHP, MySQL, and Core Java, splitting time between web application development and early Android mobile development.
Hands-on client-facing role — gathered requirements directly with clients and built desktop software with Java Swing.
Nearly three years on a product-based fintech team, where Android Architecture Components and Kotlin — as recommended by Google — became the core of day-to-day development.
Stepped up to a senior role on a product-based team, deepening expertise in Android Architecture Components and Kotlin.
Building high-quality Android apps with Jetpack (LiveData, Flow, ViewModel, Paging, Navigation, WorkManager) for a seamless UX, with performance optimized through Kotlin Coroutines. Build, test, and deployment are automated via CI/CD pipelines, using Docker for consistent development and deployment environments.
Structured transition into AI engineering alongside professional Android work — 17 certifications spanning two full specializations, agentic AI, AI agents, and cloud fundamentals, rather than a professional AI job title.
Long-term direction: applying 13+ years of software engineering rigor to AI and agentic systems, building on the Android and certification foundation above.
Honesty matters more than momentum here — this is what's professional experience, what's active learning, and what's still ahead.
13+ years professional foundation — the base the rest of this path is built on.
17 Coursera certifications (IBM, Google, Google Cloud, SkillUp) — currently learning, not yet a professional title.
Two full specializations — "Generative AI for Software Developers" and "Generative AI for Mobile App Developers" — plus several standalone courses on prompt engineering and foundation models.
Certified in "Fundamentals of Building AI Agents" from IBM.
Certified in "Agentic AI with LangChain and LangGraph" from IBM.
Not yet started — a likely next step once the agentic AI foundation is solid.
Long-term direction — not a current skill, the destination this path is aimed at.
02 — Capability
Grouped by discipline rather than ranked by bars — hover or focus any node for its status.
03 — Proof
Certifications link to their real credential where available. Nothing here is listed until it's actually earned.
3-course specialization covering generative vs. discriminative AI, prompt engineering techniques, and applying generative AI to design, bug detection, code refactoring, and optimization in software engineering.
Credential ID: 27GDNWI15GOE
4-course specialization on applying generative AI directly to mobile app development — AI-assisted design and architecture, prototyping, app design/marketing/support tooling, and an introduction to embedded AI and cloud-based mobile development.
Credential ID: IF91C9RT0QKA
Foundational course on generative AI concepts, models, and real-world applications.
Credential ID: 8XLOOS0HAWTS
Core techniques for writing effective prompts across generative AI tools.
Credential ID: 6UU7REZYIE4N
Applying generative AI tools and workflows to accelerate day-to-day software development work.
Credential ID: K4V2F699JGWG
Using generative AI tools to speed up and improve mobile app development workflows.
Credential ID: 9Z986J79PB18
Overview of major generative AI foundation models and the platforms built on them.
Credential ID: ZY42DMLMZOGV
Foundational coursework on how AI agents are designed, structured, and built.
Credential ID: R49MQXR97L89
Hands-on coursework building agentic AI workflows with LangChain and LangGraph.
Credential ID: 4AFJXTQ9FOQX
Core concepts of how modern AI tools work and how to use them effectively.
Credential ID: QEJ0G0WG05Q3
Using AI tools to support brainstorming, planning, and decision-making.
Credential ID: UQPQ9U9XGSXH
Applying AI tools to research tasks and turning findings into usable insights.
Credential ID: 7AZLV0PIE3JA
Using AI tools to improve writing and communication.
Credential ID: CQFTSK65QTRQ
Applying AI tools across content creation workflows.
Credential ID: 4GOBV62HBBN7
Using AI tools to analyze data and surface patterns faster.
Credential ID: RJGA94BOIA1X
Using AI tools to support the app building process end to end.
Credential ID: ZEOVGKTD9302
Core Google Cloud Platform infrastructure, products, and services.
Credential ID: 6D3T4I1OE2QM
Core Develocity concepts from Gradle's own training platform (DPE University) — build scans, build caching, and diagnosing build performance.
Credential ID: a0d1c981-d711-4212-bd36-4606163cfe26
Advanced into a senior engineering role at Zensar Technologies, deepening Android Architecture Components expertise.
Joined FAME Platform SDN BHD to build the POEMS Mobile 3 and POEMS Global MY trading apps.
Completed two IBM/SkillUp specializations — Generative AI for Software Developers and Generative AI for Mobile App Developers — plus standalone courses in agentic AI, AI agents, and Google Cloud fundamentals.
04 — Approach
Architecture patterns and libraries change; the underlying reasoning about state, concurrency, and failure modes doesn't. I default to understanding the primitive before reaching for the abstraction.
Code that's easy to delete, test, and hand off outlasts code that's merely clever. I optimize for the engineer reading this in a year — often me.
On mobile especially, latency and battery cost are part of the product, not an afterthought. I treat performance budgets as a design constraint, not a cleanup task.
I'm learning AI engineering because it extends what I can build — not to attach a model to a problem that didn't need one. Every AI project here starts from a concrete use case.
Working with LLMs and agentic systems means being explicit about their limits — hallucination, data handling, and failure visibility are design requirements, not edge cases.
This site draws a clear line between what I've shipped professionally and what I'm currently learning. I'd rather be precise about that boundary than inflate it.
05 — Connect
Open to conversations about Android engineering, AI engineering roles, or collaboration on applied AI projects.
Résumé last updated September 2026