Jake Moses

Software Engineer Delivering Business Impact at Amazon

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About Me

Jake Moses

Hello, I'm Jake Moses

I'm a Software Engineer at Amazon Pharmacy who bridges the gap between technology and business outcomes. I focus on understanding business challenges first, then applying AWS cloud technologies and modern development practices to create solutions that deliver measurable impact, not just code.

Based in Providence, Rhode Island, I've worked across multiple Amazon teams including Pharmacy, Last Mile Tech, and Amazon Scout, delivering high-impact solutions that enhance operational efficiency and customer experience.

What drives me is a deep curiosity about AI and its transformative potential for businesses. I take strong ownership of my projects and pride in delivering solutions that make a real difference. I'm equally passionate about understanding business use cases and working backwards from customer needs as I am about implementing the technology to support them.

Get In Touch View Resume

My Skills

Coffee and coding

Fueling my coding with coffee

AWS Cloud Services

Extensive experience with ECS Fargate, Lambda, S3, DynamoDB, CloudFormation, CloudFront, Route53, Kinesis, SQS/SNS.

Software Development

Building robust applications using Python, Java, TypeScript, and Node.js.

DevOps & Automation

Implementing CI/CD pipelines and automation solutions to improve operational efficiency.

Database Systems

Experience with database design, optimization, and management, including teaching Database Systems at UVA.

AI Integration

Leveraging Anthropic's Claude and other AI tools to enhance development workflows and solutions.

Business-Driven Solutions

Translating business requirements into technical solutions that deliver measurable impact and operational efficiency.

Agile Leadership

Leading cross-functional teams and implementing agile/scrum processes to improve productivity.

My Resume

Professional Experience

Software Engineer II - Amazon Pharmacy

October 2023 - Present | Boston, MA

  • Delivered an automation feature reducing pharmacist shift requirements by 15%, enhancing operational efficiency
  • Achieved 99% automation of machine signal tracking by leveraging AWS Lambda, DynamoDB, SNS, and Kinesis
  • Led fulfillment sad path handling for the cross-functional PillPack Packets launch, improving customer accessibility

Software Engineer II - Last Mile Tech, Amazon

November 2022 - October 2023 | Seattle, WA

  • Designed, developed, and launched two major initiatives across North America, Europe, and Japan
  • Spearheaded the development of agile/scrum processes for the team, improving productivity by 25%
  • Optimized package planning workflows utilizing AWS services, including CloudWatch, DynamoDB, Lambda, and SQS

Software Engineer I - Amazon Scout

July 2021 - November 2022 | Seattle, WA

  • Developed an AWS-deployed web application to query and dynamically label robot-generated event reports
  • Built an ecosystem of services for planning, operating, monitoring, and analyzing robotic deliveries
  • Collaborated with cross-functional teams to communicate project requirements and deliver high-impact solutions

Software Development Engineer Intern - Amazon

May 2020 - August 2020 | Seattle, WA

  • Created a web application used by different teams to query and dynamically label event reports generated by field robots
  • Deployed the application using AWS tools including Route53, Lambda, S3, CloudFront, Lambda@Edge
  • Implemented the solution with TypeScript, HTML, CSS, React JS, and Node.js

Technology Intern - Nucleus195

May 2019 - January 2020 | Stamford, CT

  • Automated client outreach processes with Python scripts, significantly improving efficiency
  • Streamlined reporting by converting spreadsheets into client-ready PDFs via Python scripts
  • Reduced the workload of repetitive tasks by implementing targeted automation solutions

Education

Bachelor of Science in Computer Engineering

Graduated May 2021 | University of Virginia, Charlottesville, VA

  • Cumulative GPA: 3.74 | CPE Major GPA: 3.84
  • Teaching Assistant in Database Systems (2 semesters), Algorithms (1 semester), and Software Testing (1 semester)
  • Mentored students in core computing concepts and graded coursework

Additional Skills & Achievements

Technical Skills

  • Coding Languages: Python3, Java, TypeScript, SQL, C++, Node.js, Git
  • AWS Services: ECS Fargate, Lambda, S3, DynamoDB, CloudFormation, CloudFront, Route53, Kinesis, SQS/SNS
  • AI/ML: Experience using Anthropic for development projects

Athletics

3-year varsity letterman and captain of the Greenwich High School golf team

For a complete overview of my experience, skills, and qualifications:

Download Full Resume

Personal Projects

Deep Research Assistant

Deep Research Assistant

An AI-powered tool that breaks down complex research questions into simpler sub-questions, answers them individually, and synthesizes the results into comprehensive explanations with interactive visualizations.

View Project GitHub Repo
Calculator Buddy

Jake's Calculator Buddy

An intelligent math tutor application that helps users solve and understand mathematical expressions with step-by-step explanations, powered by Claude AI and featuring a clean, intuitive interface.

View Project GitHub Repo
Agentic Service Bot

Agentic Service Bot

A sophisticated AI-powered smart home assistant that processes natural language requests, manages device operations, and provides responses based on customer service level permissions (Basic, Premium, or Enterprise).

View Project GitHub Repo

Project Spotlight: Deep Research Assistant

Under the Hood: How It Works

The Deep Research Assistant uses a sophisticated AI-powered approach to break down complex questions:

  1. Question Analysis: When you submit a question, the system first analyzes its complexity to determine if it needs to be broken down.
  2. Recursive Breakdown: Complex questions are intelligently divided into simpler sub-questions, which may be further broken down if needed (up to the maximum recursion depth you set).
  3. Parallel Processing: The system processes multiple sub-questions simultaneously to provide faster results.
  4. Individual Answers: Each leaf question (one that doesn't need further breakdown) receives its own detailed answer.
  5. Answer Synthesis: All individual answers are combined into a comprehensive, well-structured response to your original question.
  6. Visualization: The question tree visualization shows you exactly how your question was broken down and answered.

The system uses Claude AI (via Anthropic's API) with carefully engineered prompts to ensure high-quality, accurate, and well-structured responses. The recursive approach allows for handling questions of virtually any complexity.

Technical Implementation

Built with modern web technologies and integrated with Anthropic's Claude API, the Deep Research Assistant features:

  • Configurable parameters for maximum recursion depth and sub-questions per level
  • Interactive visualization of the question breakdown tree
  • Parallel processing for efficient handling of complex queries
  • Comprehensive answer synthesis that maintains context across all sub-questions
Try It Out View Source Code

Project Spotlight: Jake's Calculator Buddy

Intelligent Math Tutoring

Jake's Calculator Buddy is a cloud-based intelligent math tutor application that helps users solve and understand mathematical expressions. The application leverages Claude AI to provide step-by-step explanations of mathematical concepts and calculations.

Key Features

  • Intelligent Math Explanations: Powered by Anthropic's Claude AI to provide detailed explanations of mathematical expressions
  • User-Friendly Interface: Clean, intuitive design for easy interaction
  • User Tracking: Analytics for tracking user engagement and popular calculations
  • Serverless Architecture: Built on AWS services for scalability and reliability
  • Cross-Region Infrastructure: Optimized deployment across multiple AWS regions

Technical Architecture

The application is built using a modern serverless architecture on AWS:

Frontend
  • React.js single-page application
  • Responsive design for desktop and mobile devices
  • Hosted on Amazon S3 and delivered via CloudFront CDN
Backend
  • AWS Lambda functions (Python) for processing calculations
  • API Gateway for RESTful API endpoints
  • DynamoDB for user tracking and analytics
  • AWS Certificate Manager for SSL/TLS certificates
  • Route 53 for DNS management

Security Features

  • HTTPS enforced for all communications
  • API keys stored securely in AWS SSM Parameter Store
  • CORS configured to restrict access to approved domains
Try It Out View Source Code

Project Spotlight: Agentic Service Bot

Smart Home Intelligence

The Agentic Service Bot is an intelligent system that uses Claude AI to create a service-level aware approach to handling smart home device requests. Instead of treating all requests the same way, the system analyzes request complexity, validates service-level permissions, manages device operations, and provides natural language responses.

Service Tiers

  • Basic Tier: Device status checks, power control (on/off), limited to 1 device, standard support priority
  • Premium Tier: All Basic tier features plus volume control, limited to 1 device, priority support
  • Enterprise Tier: All Premium tier features plus song control, limited to 1 device, dedicated support

How It Works

  1. Request Analysis: System analyzes the type and required permissions of each request
  2. Service Level Validation: Checks if the customer's service tier allows the requested actions
  3. Device Management: Executes allowed device operations and tracks state changes
  4. Response Generation: Uses Claude AI to generate natural, context-aware responses
  5. History Tracking: Maintains conversation history for context and analysis

Technical Architecture

Built with a modern cloud-native architecture, featuring:

  • Frontend: React-based web interface with Chakra UI for a modern, responsive experience
  • Backend: AWS Lambda functions for serverless request processing
  • Real-time Communication: WebSocket API for instant responses
  • Data Persistence: DynamoDB tables for customers, service levels, messages, and connections
  • AI Integration: Claude AI for natural language understanding and generation

Key Features

  • Natural language processing of smart home device requests
  • Tiered service level system with progressive capabilities
  • Real-time device state management and tracking
  • Comprehensive conversation history
  • Intelligent upgrade suggestions based on usage patterns
Try It Out View Source Code

Get In Touch

Email

mosesjake32@gmail.com

Location

Providence, Rhode Island 02903

Phone

(203) 918-3070