APPLIED AI. BACKEND. PRODUCT THINKING.
Umair Qamar
I connect LLM application work with backend services, data flows and usable products. My focus is the software around the model, as well as the experience it enables.
LLM applications · Retrieval & data · Full-stack delivery
01 / GENAI ENGINEER
My work spans backend services, customer-data platforms and AI-enabled workflows. I bring a full-stack engineering perspective to applied AI, supported by ongoing graduate study in Artificial Intelligence at LUMS.
Source connectors, ingestion and relational modeling are part of my customer-data platform work. They provide useful engineering context for applications that depend on well-structured information.
Explore data engineering ↗JobSprint OS is my personal product, built iteratively with AI assistance. It demonstrates connected workflows, product decisions and explicit approval boundaries, not an autonomous agent platform.
Explore product decisions ↗My toolkit includes RAG, embeddings, semantic search, Pinecone and FAISS. My master’s in AI is in progress; it complements my software engineering experience.
View education & credentials ↗02 / SELECTED ENGINEERING WORK
The context, my contribution,
and the decisions underneath.
03 / EXPERIENCE ACROSS STAGES
Scope changes.
Ownership still matters.
Senior Software Engineer / Tech Lead
I contribute hands-on engineering and technical leadership to SRG's Australian retail engagement through Convert Digital. Working within an established engineering ecosystem means connecting implementation decisions with the wider product, the teams around it and the systems already in use.
This is engineering with enterprise constraints: interconnected systems, performance-sensitive customer experiences and changes that need to be delivered safely. Reliability, maintainability and clear technical decisions shape how I approach the work.
A multi-brand retail group spanning Spotlight, Anaconda, Harris Scarfe and Mountain Designs. That breadth brings a different delivery context from building a startup's first product.
Group context, not a claim of ownership across every brand or system.
I joined as the first full-stack engineer from Pakistan before the startup had its first customers. My work spanned backend services, cloud infrastructure and data-platform engineering as the company grew.
Alongside hands-on development, I led engineering teams and helped connect technical decisions with product delivery.
Earlier roles built my foundation across frontend and backend development, from React interfaces and API integrations to Node.js services, authentication and application workflows.
04 / MY ENGINEERING TOOLKIT
Across the interface, the services
and the infrastructure underneath.
A toolkit, not a fixed recipe. I choose technologies around the product, the team's needs and the constraints of the system.
Connecting LLM applications with useful context through ingestion, chunking, embeddings and retrieval.
Operational data, caching and analytical storage.
APIs, microservices and asynchronous systems.
Serverless workflows, containers and infrastructure as code.
Interfaces, application state and connected workflows.
05 / HOW I LEAD DELIVERY
Good technical leadership makes
the next decision clearer.
Make the user need, constraints and success criteria explicit before choosing a solution.
Connect the interface, service boundaries, data model and infrastructure into a coherent plan.
Work through the difficult implementation details and help the team move with shared context.
Bring testing, rollout and operational feedback into the conversation, not just feature completion.
06 / ALWAYS BUILDING, ALWAYS LEARNING
Hands-on engineering experience, AWS credentials and formal study in AI.
Solutions Architect credential ↗
Cloud Practitioner credential ↗
Lahore University of Management Sciences (LUMS). In progress.
University of Engineering and Technology, Lahore.
