Recommended expert
Abdul (Wahab) Khan
Software Engineer
Experience
Dec 2024 - Nov 2025
1 yearSoftware Engineer
EdgeFirm
- Designed and developed end-to-end web and mobile products as a full-stack engineer, working across Python/FastAPI backends, databases, and React / React Native frontends.
- Built LLM- and agentic-AI systems using LangChain, LangGraph, CrewAI, Langfuse, and vector databases, focusing on reliability, observability, and clean abstractions.
- Developed a text-to-SQL assistant for the marketing team that lets non-technical users query a large retail-style dataset in natural language, returning clear analytics and campaign insights.
- Helped reduce ad-hoc SQL/reporting requests to engineering by 60% and cut time-to-insight for common marketing queries from hours to minutes.
- Created a full-stack mobile app where Apple Health data is processed and fed into an LLM to generate personalised, VO2-max–based health coaching and insights, owning architecture from frontend to backend and auth.
Jul 2022 - Sep 2022
3 monthsKarachi, Pakistan
HybridSoftware Engineer Intern
Sybrid Private Limited (Lakson Group)
- Wrote clean, maintainable code for hybrid mobile applications using React Native with a single shared codebase.
- Handled frontend, simple backend logic, and REST API integration to deliver end-to-end features.
- Worked within an engineering team, gaining experience with version control, code reviews, and production-focused development practices.
Text-to-SQL Multi-Agent Backend for Marketing Analytics
SQLSenseBot
- Developed a production-ready API backend for a multi-agent text-to-SQL assistant used by the marketing department to self-serve analytics on campaign, spend, and performance data.
- Orchestrated agents in LangGraph to interpret schema, generate safe SQL, and return natural-language answers and charts.
- Reduced manual dashboard/report creation effort by approximately 50% and enabled marketers to answer most day-to-day questions without engineering support, with full tracing and evaluation via Langfuse.
Full-Stack AI Health Coaching App
StrideIQ
- Built a mobile app that ingests Apple Health data and uses an LLM to generate personalised coaching plans and VO2-max–based health insights.
- Implemented secure authentication, health-data sync, and a FastAPI backend with RAG-style context and observability (logging, tracing, evaluation of LLM outputs).
Skills
Languages
- Python
- Javascript
- Typescript
- Sql
Frontend
- React
- Next.js
- React Native
- Html5
- Css3
- Tailwind Css
- Shadcn/ui
Backend
- Fastapi
- Node.js
- Express
- Nestjs
- Restful Apis
- Websockets
Databases
- Postgresql
- Mongodb
- Sqlite
- Vector Databases (E.g., Pinecone)
Ai / Llms
- Llms
- Rag
- Embeddings
- Agents
- Prompt Engineering
- Langchain
- Langgraph
- Crewai
- Langfuse
Devops & Tools
- Docker
- Git
- Github
- Github Actions
- Linux
- Postman
Workflow
- Clean Code
- System Design
- Observability (Logging, Tracing, Evaluation)
- Agile / Scrum
Languages
Urdu
NativeEnglish
AdvancedEducation
Oct 2025 - Nov 2027
University of Passau
Master of Science, Artificial Intelligence Engineering · Artificial Intelligence Engineering · Passau, Germany
Aug 2020 - Jun 2024
National University of Computer and Emerging Sciences (FAST-NUCES)
Bachelor of Science, Computer Software Engineering · Computer Software Engineering · Karachi, Pakistan
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