Kerry Dor

AI & Machine Learning Engineer

Full-stack Engineer

Everett, MA, US

Django

MongoDB

MySQL

CodeIgniter

Laravel

PHP

AngularJS

Vue.js

PostgreSQL

TypeScript

Node.js

Next.js

React

Tensorflow

PyTorch

Kubernetes

Terraform

Tableau

Amazon S3

Jenkins

Docker

Data Engineering

SQL

JSON

CI/CD

Observability

EMR

Slack

Python

Airflow

Amazon Kinesis

Apache Spark

Microsoft Azure

Amazon Redshift

Apache Kafka

REST

DevOps

ETL

Linux

Github

Git

UNIX

Database Design

Analytics

AWS Step Functions

AWS Glue

Amazon SNS

Amazon DynamoDB

MS SQL

Amazon SQS

AWS Lambda

Available for hire fromNegotiable

Senior AI/Fullstack Engineer | 7+ Years in Fintech & Banking etc Platforms

I’m a full‑stack engineer specializing in building production‑ready AI systems that combine strong software engineering with practical machine intelligence. My work spans end to end product development from designing clean, scalable backend architectures to shipping polished frontend experiences with a particular focus on integrating LLMs, automation, and intelligent workflows into real applications. I’ve built systems that process large, fast moving data streams, orchestrate multi agent AI pipelines, and automate complex business operations with reliability and low latency. I enjoy roles where I can move between architecture, implementation, and iteration, turning ambiguous ideas into working software that feels fast, stable, and thoughtfully engineered. Whether I’m building internal tools, customer facing products, or AI‑powered automation, I care about clarity, maintainability, and delivering features that actually move the needle for the business.

Projects

DrinkXie

DrinkX (drinkxie.com) is a performance‑driven growth platform for the beverage industry, designed to help suppliers, retailers, and distributors acquire customers, drive digital sales, and stay compliant with three‑tier regulations. The platform combines AI‑powered user acquisition, SKU‑level promotion tools, and post‑purchase re‑engagement systems to help beverage brands grow measurable, margin‑aware demand.See More

Ellis Brigham

Ellis Brigham is a UK‑based outdoor retail brand specializing in high‑performance clothing, footwear, and equipment for hiking, climbing, skiing, mountaineering, trail running, camping, and general outdoor adventure. The platform serves as a full e‑commerce destination for premium outdoor gear, featuring top global brands and expert‑curated collections.See More

Uizard

Uizard is an AI‑powered design and prototyping platform that allows users to create app interfaces, websites, dashboards, and product mockups instantly using natural language, sketches, or screenshots. It’s built for speed, collaboration, and non‑designers who need production‑ready UI concepts without deep design skills.See More

ITDorServices

IT Dor Services is a global, remote‑first software development and application support company that builds custom web, mobile, AI, and cloud solutions while also providing dedicated post‑launch support. Their core value proposition is one integrated team that handles both development and ongoing application support, eliminating the typical gap between builders and maintainers.See More

Work History

Senior AI & Fullstack Engineer

Kanda SoftwareFull-time EmployeeApr 2023 - May 2024 • 1 yr 2 mosDesigned and built backend systems, distributed pipelines, and intelligent automation powering pricing, invoicing, and customer usage analytics across digital banking products. • Engineered a usage based billing platform that ingests high volume API/session activity, processes it through PySpark on EMR, and exposes structured datasets for downstream AI and analytics workflows. • Designed backend architecture across Kinesis, Firehose, S3, Airflow, and Step Functions, implementing rating, proration, and invoice generation logic as modular, fault tolerant services. • Designed a fraud scoring feature store serving engineered signals such as device velocity metrics, geolocation mismatch flags, and behavioral patterns using S3 + Glue Catalog. Standardized feature computation and storage to significantly reduce model training data preparation time. • Built recovery and validation workflows using SQS, Lambda, and DynamoDB to ensure correctness, prevent double billing, and provide operational transparency through automated reconciliation alerts. • Developed a Redshift billing warehouse with optimized schema patterns to support real time dashboards, reporting, and data driven product insights. Fraud, Risk & Decisioning Feature Platform — Lending & Financial Operations Built AI ready feature pipelines and data services supporting fraud detection, onboarding, and decisioning systems. • Designed a feature store that standardizes engineered signals such as device velocity patterns, behavioral indicators, and geolocation mismatches using S3 + Glue Catalog. • Streamlined feature computation and retrieval to accelerate model iteration and ensure consistent inputs for AI driven scoring and decisioning workflows. Environments: Node.js, TypeScript, Python, PySpark, React/Next.js, AWS (Kinesis, Firehose, S3, EMR, Glue, Athena, Redshift, Lambda, Step Functions, SQS, SNS), Airflow, Docker, Terraform, Git, Postgres, Redis, Parquet, JSON

Senior Fullstack Developer

HatchWorksFull-time EmployeeJan 2022 - Feb 2023 • 1 yr 2 mosInternal platforms supporting mortgage application processing, underwriting workflows, pricing evaluation, borrower-journey insights, and operational reporting. • Developed and maintained backend services and ETL components that transformed complex loan-application JSON into normalized, analytics-ready datasets, implementing PySpark logic to flatten nested borrower, property, and income structures while handling malformed records. • Built service integrations that linked application, underwriting, and closing events across multiple systems using deterministic identity logic, enabling consistent borrower-journey tracking and funnel analysis. • Extended pricing and evaluation services to support new lending products by updating schemas, enriching backend logic, and backfilling historical data for downstream systems and analytics teams. • Optimized key Athena workloads by restructuring queries, improving partition pruning, and tuning Parquet layout to improve reporting performance during peak cycles. • Refactored Spark jobs suffering from skewed joins by introducing key-salting and broadcasting small lookup tables, stabilizing memory usage and improving job reliability across data-processing pipelines. Environments: Python, PySpark, Node.js, SQL, AWS (S3, EMR, Glue, Athena), Airflow, Terraform, Docker, Git, Iceberg, Parquet, JSON

Junior AI Developer | Former Intern

Andersen LabFull-time EmployeeMar 2019 - Nov 2021 • 2 yrs 9 mosFinancial Data Automation & Intelligence Systems — Internal Finance Platforms Built automation scripts, backend services, and data processing workflows that supported financial reporting, reconciliation, and operational analytics across internal finance applications. • Automated a monthly financial reconciliation workflow by converting manual SQL queries and Python data prep steps into a scheduled job, enabling consistent, repeatable data processing for downstream analytics and model ready datasets. • Replaced a legacy CSV based data exchange between two internal finance systems with a JSON based REST API, improving data quality, enabling structured validation, and laying groundwork for future AI driven data checks. • Diagnosed and resolved a production pipeline issue caused by late arriving reference data; added freshness checks and automated alerts to ensure upstream data reliability for downstream analytical and ML ready processes. • Enhanced deployment automation (Jenkins + shell scripts) by adding unit tests for SQL transformation logic, improving reliability of data pipelines used for reporting and feature generation. Environments: Python, SQL Server, REST APIs, AWS, Azure, Jenkins, Git/GitHub, Bash, JSON

Education

Boston University

Bachelor's Degree, Computer Science2014 - 2018

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