Applied AI × Software Engineering

Building AI systems that are useful, grounded & shippable.

I’m Insha Yaqoob—an Applied AI and Python engineer in Milan. I combine 2+ years of production backend experience with hands-on work in RAG, AI agents, semantic search and full-stack product development.

Open to AI, GenAI and Python engineering opportunities across Italy & remote
PythonLangChainRAGAI AgentsDjangoPostgreSQLReact
01 / SELECTED WORK

From models to meaningful products.

Projects where retrieval, orchestration and software architecture work together—built around user value and reliability.

MEDAGENT / HEALTHCARE AI
DOCSFAISSRAGANSWER
Grounded healthcare information

MedAgent

An end-to-end clinical information assistant designed to answer questions from supplied medical documents through retrieval-augmented generation.

  • Built semantic retrieval with LangChain and FAISS vector storage.
  • Focused on source-grounded answers and reducing unsupported output.
  • Explored reliability, data quality and human oversight in healthcare AI.
PYTHONLANGCHAINFAISSRAGOPENAI API
RESEARCH CODEY / AGENTIC AI
GOALTOOLSAGENTOUTPUT
Research and code intelligence

Research Codey

An AI-assisted workflow exploring how agents combine retrieval, tool use and structured reasoning to support research and code-oriented tasks.

  • Designed multi-step agent workflows around concrete user goals.
  • Integrated APIs and structured responses into a maintainable Python workflow.
  • Applied rapid prototyping and evaluation to improve usefulness.
AI AGENTSPYTHONAPIsSEMANTIC SEARCH
FUTURESYNC / AUTOMATION
INPUTWORKFLOWAUTOMATIONRESULT
Human-centred automation

FutureSync

A product-oriented experiment coordinating AI capabilities and software workflows to turn ambiguous requests into structured actions.

  • Translated open-ended needs into discrete, testable workflow steps.
  • Combined LLM behaviour with conventional application logic.
  • Built with iteration, clarity and user value as design constraints.
LLMsWORKFLOWSPROTOTYPINGFULL STACK
02 / HACKATHONS

Fast builds. Real competition. Proven results.

International hackathons strengthened my ability to scope quickly, collaborate under pressure and turn unfamiliar technologies into working products.

TOP 5

Autonomous Agents Hackathon

Finalist for an agent-based solution built through rapid experimentation.

WIN

WebGPU Challenge

Winner of a technical challenge using modern GPU-powered web technology.

03 / EXPERIENCE

Production foundations, AI direction.

My AI work is grounded in real software delivery: requirements, APIs, databases, testing, debugging and product collaboration.

PROFESSIONAL

Associate Software Engineer · Naive Sprint

Developed Python/Django and PostgreSQL applications, REST APIs, operational workflows, reporting tools and integrations for a US transportation client. Collaborated with frontend, QA and business stakeholders; tested releases, resolved defects and documented changes.

Django Developer · MicroStarX

Developed Django REST services, relational data models and backend features integrated with React interfaces. Performed functional testing, debugging and query optimisation.

2025 — 2027
MSc Artificial Intelligence for Science and TechnologyUniversità degli Studi di Milano-Bicocca · In progress
2020 — 2024
Bachelor’s in Software EngineeringUniversity of Agriculture Faisalabad · GPA 3.64/4.00
04 / EXPERTISE

A practical AI toolkit.

Comfortable moving across the stack—from retrieval quality and model experiments to APIs, data models and interfaces.

01

Generative AI

LLMs, RAG, prompt engineering, semantic search, tool use, AI agents and grounded generation.

02

AI & Data

Python, pandas, NumPy, scikit-learn, TensorFlow/Keras, NLP and model evaluation.

03

Backend Engineering

Django, FastAPI, Flask, REST APIs, PostgreSQL, MySQL, data modelling and integrations.

04

Product Delivery

React, JavaScript, Git, testing, documentation, Agile teamwork, debugging and requirements analysis.

Looking for an engineer who can bridge AI and production software?