Mohammad El Prince

Mohammad El Prince

Agentic AI Software Engineer

About Me

Mohammad El Prince

Mohammad

Software Development at Amazon

I'm a software engineer with a data background who builds and ships production systems on AWS — retrieval-augmented and agentic AI applications, serverless platforms, and type-safe full-stack products. I own engineering end to end, from architecture through production.

Flexible with timezones

Based in Milton, ON, available globally

Certifications

Amazon Web Services

Certified

2 AWS certifications: AWS Solutions Architect Associate · AWS Cloud Practitioner

Flatiron School

Graduate

Full Stack Web Development — Python & JavaScript

Available for work

Have a vision?Let's build it

together.

Resume
Verily, Allah loves that when any one of you does a job, he perfects it.
Prophet Muhammad ﷺ
  • 15+Serverless applications shipped
  • 8+Locations served
  • 2+Years of experience
  • 20+Technologies

Experience

  1. Present

    AI Engineering Focus

    Amazon

    Extending serverless and backend expertise into AI engineering — RAG, LLM applications, agents, retrieval pipelines, tool calling, and evaluation.

    RAG · LLM Agents · Retrieval Pipelines · Evaluation

  2. 02/2025 – Present

    Data Analyst — Software Development Focus

    Amazon

    Building serverless applications and a multi-region quality management platform (React 19, TypeScript, tRPC, AWS CDK) serving managers at North American fulfillment centers.

    React 19 · TypeScript · tRPC · AWS CDK

  3. 02/2023 – 10/2023

    Full Stack Web Development

    Flatiron School

    Full Stack Web Development online program in Python and JavaScript.

    Python · JavaScript · React · Full-Stack

  4. 2021 – 2024

    Operations

    Amazon

    Operations roles across multiple Ontario locations (Hamilton, St. Thomas, London, Mississauga) before transitioning to software development.

    Operations · Leadership · Process Improvement

  5. 01/2019 – 02/2021

    Master of Engineering — Mechanical Engineering

    University of Guelph

    Course-based Master of Engineering in Mechanical Engineering in Guelph, ON.

    Mechanical Engineering · Data Analysis · Research

Skills

Backend

  • TypeScript
  • Python
  • Node.js
  • tRPC
  • Vitest
  • Git
  • Nx
  • ESLint
  • Prettier

Frontend

  • React 19
  • JavaScript
  • HTML/CSS
  • Vite

Cloud

  • AWS Lambda
  • CDK
  • S3
  • CloudFront
  • EventBridge
  • SES
  • SNS
  • CloudWatch
  • RUM
  • WAF
  • Route 53
  • Infrastructure as Code

AI

  • Retrieval-Augmented Generation
  • LLM Applications
  • Agents
  • Retrieval & Embedding Pipelines
  • Tool Calling
  • Evaluation Pipelines

Databases

  • DynamoDB
  • SQL

AI Engineering

  • Retrieval-Augmented Generation

    Described competency

    Grounding language-model responses in external knowledge by retrieving relevant context at query time — applied in Noor AI, where answers cite whole Quran verses and Bukhari hadith retrieved from a ~27,000-chunk Bedrock Knowledge Base, with citations drawn from metadata so the model cannot fabricate references.

    • AWS Bedrock Knowledge Bases
    • S3 Vectors
    • Cohere Multilingual v3
    • LangChain
  • LLM Applications

    Described competency

    Designing production application flows around large language models — prompt design, token-by-token streaming, context management, and guardrails. Noor AI streams Claude responses end to end through a FastAPI Lambda behind CloudFront, with a system prompt that enforces citation and madhab-accuracy rules.

    • AWS Bedrock (Claude)
    • FastAPI
    • Response Streaming
    • Prompt Engineering
  • Agents

    Described competency

    Composing agent workflows that plan, call tools, and iterate toward a goal with explicit state and stopping conditions. Noor AI runs a LangChain tool-calling agent on Bedrock Claude that decides when to retrieve grounded passages and keeps per-session conversation memory in DynamoDB.

    • LangChain Agents
    • Tool Calling
    • DynamoDB Memory
  • Retrieval & Embedding Pipelines

    Described competency

    Building ingestion and embedding pipelines that chunk source content, generate vector embeddings, and index them for semantic retrieval. Noor AI's offline pipeline transforms the Quran and Sahih al-Bukhari into ~27,000 single-chunk files with precomputed citation metadata, embedded into an S3 Vectors index.

    • Python
    • Embedding Pipelines
    • S3
    • Citation Metadata
  • Tool Calling

    Described competency

    Exposing typed functions and external APIs to a language model so it can invoke them with validated arguments. Noor AI wraps the Bedrock Knowledge Base Retrieve API as a LangChain tool the agent calls on demand, mapping model intents onto real retrieval actions.

    • LangChain Tools
    • Bedrock Retrieve API
    • Python
  • Evaluation Pipelines

    Described competency

    Measuring model and application quality through automated evaluation harnesses — golden datasets, regression checks, and scoring metrics — applying the 100% test-coverage discipline maintained on the Quality Management Platform to non-deterministic systems.

Engineering Excellence

  • System Design

    Designing full-stack systems end to end — from edge authentication and type-safe APIs to data modeling and analytics — for the Quality Management Platform serving managers across North American fulfillment centers.

    • Designed a TypeScript monorepo (React 19, tRPC, AWS CDK) with a serverless API layer and CDN-based authentication.
    • Implemented edge-level authentication, role-based access control, and real-time user monitoring.
    • Built analytics dashboards with multi-location filtering and manager-level data aggregation.
    • AWS Lambda
    • CloudFront
    • DynamoDB
  • Scalability

    Building event-driven, serverless workloads that scale to production traffic across multiple locations without managing servers.

    • Developed 15+ serverless data-automation tools processing operational data from S3 and internal APIs.
    • Delivered real-time alerts via SES, SNS, and Slack to operations teams.
    • Launched the platform MVP at a pilot location and expanded toward 8+ additional fulfillment centers.
    • AWS Lambda
    • EventBridge
    • SES
    • SNS
    • S3
  • Cloud Architecture

    Architecting and deploying a multi-region web platform entirely as infrastructure-as-code, reproducible through AWS CDK with automated CI/CD.

    • Provisioned a multi-region footprint through AWS CDK infrastructure as code.
    • Owned the full lifecycle from architecture design through CI/CD deployment and production monitoring.
    • Configured CDN delivery, edge authentication, and observability for production workloads.
    • CDK
    • CloudFront
    • CloudWatch
    • Route 53
    • WAF
  • AWS Services

    Hands-on depth across the AWS serverless and infrastructure stack used to run the platform and data-automation tools in production.

    • Compute and APIs on AWS Lambda with tRPC and DynamoDB persistence.
    • Messaging and notifications through EventBridge, SES, and SNS.
    • Edge delivery and security via CloudFront, WAF, and Route 53, with monitoring through CloudWatch and RUM.
    • AWS Lambda
    • DynamoDB
    • S3
    • CloudFront
    • EventBridge
    • SES
    • SNS
    • CloudWatch
    • RUM
    • WAF
    • Route 53
  • Backend Engineering

    Writing type-safe, well-tested backend services in TypeScript and Python, owning the software lifecycle from requirements through production monitoring.

    • Built type-safe tRPC APIs backed by DynamoDB with role-based access control.
    • Maintained 100% test coverage across 6 packages using Vitest, ESLint, and snapshot testing.
    • Automated CI/CD pipelines for repeatable, infrastructure-as-code deployments.
    • AWS Lambda
    • DynamoDB

Ready to Connect?

Let's turn your next idea into something real

From idea to impact

Let's build something real.

Open to full-time roles & freelance projects

I build high-performance applications that turn complex ideas into seamless user experiences.