Taimoor Saqib
@taimoorsaqib
Software engineer leveraging AI/ML infrastructure and data engineering to ship RLHF and real-time platforms.
What I'm looking for
I’m a software engineer with 4+ years of experience across AI/ML infrastructure, data engineering, and fullstack development. At Turing (OpenAI), I proposed, designed, and built an agentic pre-labeling system using LangChain and LangGraph that auto-populates RLHF fields before human review, shifting workflows from label-from-scratch to verify-and-correct. I also architected confidence-gated routing, shipped auto-escalation for annotator disagreement, reduced total annotator hours by 3x, and improved API p95 response times from 1.2s to 280ms.
Earlier, at Kavtech, I designed and operated 100+ AWS ETL jobs, replacing manual ingestion with serverless pipelines to reduce freshness lag from 24 hours to under 15 minutes, and achieved 99.9% job success using CloudWatch monitoring and automated retries. Before that at I2C, I optimized slow legacy database workflows, built automated SLA tracking and escalation, and improved Tier-1 resolution times by 20%. I carry the same mindset into my projects—building deterministic, validated AI pipelines (RAG, RLHF, and local LLM tooling) that prioritize reliability, debuggability, and measurable outcomes.
Experience
Work history, roles, and key accomplishments
Software Engineer
Turing (OpenAI)
Sep 2023 - Present (2 years 9 months)
Designed and built an agentic pre-labeling system for RLHF workflows using LangChain/LangGraph, reducing total annotator hours by 3x by auto-populating structured labels and confidence-gated routing. Improved labeling data quality by reducing contamination from ~12% to ~4% and optimized platform API performance (p95 1.2s to 280ms), while leading a 6-engineer team and deploying real-time validation
Data Engineer
Kavtech
Sep 2022 - Sep 2023 (1 year)
Built and operated 100+ scheduled AWS ETL pipelines ingesting Google LSA and Facebook Ads data into a centralized PostgreSQL warehouse, reducing data freshness lag from 24 hours to under 15 minutes. Delivered reliable, client-ready analytics by deduplicating and normalizing multi-source ad datasets with PySpark and achieving 99.9% job success using CloudWatch/SNS monitoring and retries, supporting
Software Engineer
I2C
Aug 2021 - Sep 2022 (1 year 1 month)
Served as a primary technical contact for overseas financial services clients, performing root-cause analysis on payment processing systems and optimizing legacy Informix query performance to reduce report generation time from 45+ minutes to under 8 minutes. Built automated SQL/Linux cron-based SLA tracking with escalation, documented APIs via runbooks to reduce Tier-1 resolution time by 20%, and
Education
Degrees, certifications, and relevant coursework
National University of Computer and Emerging Sciences
Bachelor of Science, Computer Science
2017 - 2021
Earned a BS in Computer Science from the National University of Computer and Emerging Sciences between 2017 and 2021.
Tech stack
Software and tools used professionally
Facebook Ads
GitHub
Pandas
PySpark
MySQL
PostgreSQL
Gmail
Node.js
Next.js
Redis
JavaScript
Java
JSON
Streamlit
Gradio
FastAPI
SQLAlchemy
CentOS
Linux
Gemini
Prisma
AWS Lambda
Serverless
Time Analytics
Root Cause
s3-lambda
SQL
Hugging Face
LangChain
Ollama
ChromaDB
OpenAI API
Google Gemini API
Score
Zod
Agentic
LangGraph
DeepSeek
Task
Remote
Availability
Location
Authorized to work in
Portfolio
github.com/taimoorsaqib1Job categories
Skills
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