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I’m James O’Rourke, a Senior AI & Full-Stack Engineer with 7+ years delivering production AI systems and scalable web platforms across NLP, intelligent document processing, and data-driven applications. I specialize in Python, Node.js, TypeScript, React, and Next.js, and I deploy cloud-native services on AWS using Docker, Kubernetes, and Infrastructure as Code. I have hands-on experience building LLM-powered applications with retrieval-augmented generation (RAG), vector search, and API-driven microservices. I design end-to-end machine learning pipelines—from data engineering and model training to CI/CD, monitoring, and drift detection—while prioritizing clean code, robust backend architecture, and cross-functional collaboration to improve reliability, latency, and cost in production. I thrive in cross-functional teams, partner with product and design stakeholders to translate business needs into scalable technical solutions, and continuously push for measurable improvements in accuracy, performance, and operational efficiency.…I’m James O’Rourke, a Senior AI & Full-Stack Engineer with 7+ years delivering production AI systems and scalable web platforms across NLP, intelligent document processing, and data-driven applications. I specialize in Python, Node.js, TypeScript, React, and Next.js, and I deploy cloud-native services on AWS using Docker, Kubernetes, and Infrastructure as Code. I have hands-on experience building LLM-powered applications with retrieval-augmented generation (RAG), vector search, and API-driven microservices. I design end-to-end machine learning pipelines—from data engineering and model training to CI/CD, monitoring, and drift detection—while prioritizing clean code, robust backend architecture, and cross-functional collaboration to improve reliability, latency, and cost in production. I thrive in cross-functional teams, partner with product and design stakeholders to translate business needs into scalable technical solutions, and continuously push for measurable improvements in accuracy, performance, and operational efficiency.

James O'Rourke

Full Stack Developer, Data Scientist, AI Engineer, +2

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I’m James O’Rourke, a Senior AI & Full-Stack Engineer with 7+ years delivering production AI systems and scalable web platforms across NLP, intelligent document processing, and data-driven applications. I specialize in Python, Node.js, TypeScript, React, and Next.js, and I deploy cloud-native services on AWS using Docker, Kubernetes, and Infrastructure as Code. I have hands-on experience building LLM-powered applications with retrieval-augmented generation (RAG), vector search, and API-driven microservices. I design end-to-end machine learning pipelines—from data engineering and model training to CI/CD, monitoring, and drift detection—while prioritizing clean code, robust backend architecture, and cross-functional collaboration to improve reliability, latency, and cost in production. I thrive in cross-functional teams, partner with product and design stakeholders to translate business needs into scalable technical solutions, and continuously push for measurable improvements in accuracy, performance, and operational efficiency.…I’m James O’Rourke, a Senior AI & Full-Stack Engineer with 7+ years delivering production AI systems and scalable web platforms across NLP, intelligent document processing, and data-driven applications. I specialize in Python, Node.js, TypeScript, React, and Next.js, and I deploy cloud-native services on AWS using Docker, Kubernetes, and Infrastructure as Code. I have hands-on experience building LLM-powered applications with retrieval-augmented generation (RAG), vector search, and API-driven microservices. I design end-to-end machine learning pipelines—from data engineering and model training to CI/CD, monitoring, and drift detection—while prioritizing clean code, robust backend architecture, and cross-functional collaboration to improve reliability, latency, and cost in production. I thrive in cross-functional teams, partner with product and design stakeholders to translate business needs into scalable technical solutions, and continuously push for measurable improvements in accuracy, performance, and operational efficiency.

Available to hire

I’m James O’Rourke, a Senior AI & Full-Stack Engineer with 7+ years delivering production AI systems and scalable web platforms across NLP, intelligent document processing, and data-driven applications. I specialize in Python, Node.js, TypeScript, React, and Next.js, and I deploy cloud-native services on AWS using Docker, Kubernetes, and Infrastructure as Code. I have hands-on experience building LLM-powered applications with retrieval-augmented generation (RAG), vector search, and API-driven microservices. I design end-to-end machine learning pipelines—from data engineering and model training to CI/CD, monitoring, and drift detection—while prioritizing clean code, robust backend architecture, and cross-functional collaboration to improve reliability, latency, and cost in production.

I thrive in cross-functional teams, partner with product and design stakeholders to translate business needs into scalable technical solutions, and continuously push for measurable improvements in accuracy, performance, and operational efficiency.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Language

English

Fluent

Work Experience

Senior AI/ML Software Engineer at Hyperscience

July 1, 2024 - Present

Leading AI and full-stack delivery of document understanding and LLM-powered features, building scalable Python services and cloud-native applications with strong MLOps and observability. Architected document understanding pipelines combining OCR signals and transformer-based NLP models, and implemented retrieval-augmented generation workflows with auditable guardrails for enterprise processing. Built inference services on Kubernetes with queue-based batching to stabilize latency during peak document ingestion. Exposed capabilities to front-ends via REST APIs and authentication layers. Implemented end-to-end observability with OpenTelemetry and Prometheus, and established CI/CD pipelines with Terraform-based infrastructure. Partnered with stakeholders to align evaluation targets and release milestones. Mentored engineers on clean architecture and testing.

Machine Learning Engineer at Corti

January 1, 2022 - June 1, 2024

Developed and productionized healthcare NLP and speech recognition systems, building reproducible ML pipelines using MLflow and Kubeflow, backend APIs, and Kubernetes-based deployments with strong evaluation rigor. Improved clinical language model quality through systematic error analysis and domain-guided data curation. Productionized PyTorch inference behind REST APIs with batching, caching, and quantization. Implemented staged deployments with model registry validation checks and Kubernetes rollouts. Built streaming data integrations using Kafka and Airflow for real-time transcription and analytics. Collaborated with frontend and product teams to expose NLP outputs through secure API contracts. Mentored junior engineers on testing, reproducibility, and incident postmortems.

Data Scientist at Sentiance NV

June 1, 2019 - December 1, 2021

Built machine learning models and data pipelines for on-device mobility analytics, focusing on sensor feature engineering, scalable ETL, and production-ready datasets. Trained gradient-boosted and deep learning models; formalized error analysis workflows to guide iterative model improvements. Developed SQL-based ETL processes and Airflow orchestration, producing analytics-ready datasets with documented lineage. Collaborated with product stakeholders to define quality thresholds and false-positive tradeoffs. Automated data quality monitoring reports tracking feature drift and distribution shifts, reducing diagnosis time during production incidents. Packaged trained models and metadata artifacts for backend integration, ensuring reproducible scoring workflows across staging and production.

Software Engineer Intern at Tapfiliate B.V.

February 1, 2019 - May 1, 2019

Contributed to backend SaaS analytics and affiliate tracking systems, implementing reliable APIs, event processing, and cloud-based deployments on AWS. Implemented backend REST API enhancements for affiliate conversion tracking, enforcing idempotent event handling and stricter validation rules. Built ETL workflows transforming raw tracking events into PostgreSQL analytics tables, reducing manual reporting overhead. Optimized dashboard performance with Redis caching and PostgreSQL indexing strategies. Containerized backend services with Docker and deployed to AWS, supporting consistent staging and production configurations. Expanded unit and integration test coverage within CI/CD pipelines, decreasing regression risk during weekly feature releases.