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I am a software engineer with 11+ years of experience leading full-stack AI/ML development in startup and enterprise environments. I specialize in building and deploying large-scale NLP, LLM, and computer vision systems on cloud platforms (AWS, GCP, Azure) with modern DevOps practices (Docker, Kubernetes, CI/CD). I have a proven track record of driving product vision and scalability, including spearheading AI initiatives in healthcare to deliver secure, HIPAA-compliant solutions.\n\nI focus on LLM orchestration and multi-agent architectures using LangChain and LangGraph, translating complex requirements into technical architectures, mentoring engineering teams, and delivering high-impact AI products end-to-end. My work spans secure data pipelines, retrieval-augmented generation, and autonomous tool-enabled agent coordination, with a strong emphasis on production-readiness and measurable impact.…I am a software engineer with 11+ years of experience leading full-stack AI/ML development in startup and enterprise environments. I specialize in building and deploying large-scale NLP, LLM, and computer vision systems on cloud platforms (AWS, GCP, Azure) with modern DevOps practices (Docker, Kubernetes, CI/CD). I have a proven track record of driving product vision and scalability, including spearheading AI initiatives in healthcare to deliver secure, HIPAA-compliant solutions.\n\nI focus on LLM orchestration and multi-agent architectures using LangChain and LangGraph, translating complex requirements into technical architectures, mentoring engineering teams, and delivering high-impact AI products end-to-end. My work spans secure data pipelines, retrieval-augmented generation, and autonomous tool-enabled agent coordination, with a strong emphasis on production-readiness and measurable impact.

Richard Brawley

Developer, Full Stack Developer, AI Engineer, +2

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I am a software engineer with 11+ years of experience leading full-stack AI/ML development in startup and enterprise environments. I specialize in building and deploying large-scale NLP, LLM, and computer vision systems on cloud platforms (AWS, GCP, Azure) with modern DevOps practices (Docker, Kubernetes, CI/CD). I have a proven track record of driving product vision and scalability, including spearheading AI initiatives in healthcare to deliver secure, HIPAA-compliant solutions.\n\nI focus on LLM orchestration and multi-agent architectures using LangChain and LangGraph, translating complex requirements into technical architectures, mentoring engineering teams, and delivering high-impact AI products end-to-end. My work spans secure data pipelines, retrieval-augmented generation, and autonomous tool-enabled agent coordination, with a strong emphasis on production-readiness and measurable impact.…I am a software engineer with 11+ years of experience leading full-stack AI/ML development in startup and enterprise environments. I specialize in building and deploying large-scale NLP, LLM, and computer vision systems on cloud platforms (AWS, GCP, Azure) with modern DevOps practices (Docker, Kubernetes, CI/CD). I have a proven track record of driving product vision and scalability, including spearheading AI initiatives in healthcare to deliver secure, HIPAA-compliant solutions.\n\nI focus on LLM orchestration and multi-agent architectures using LangChain and LangGraph, translating complex requirements into technical architectures, mentoring engineering teams, and delivering high-impact AI products end-to-end. My work spans secure data pipelines, retrieval-augmented generation, and autonomous tool-enabled agent coordination, with a strong emphasis on production-readiness and measurable impact.

Available to hire

I am a software engineer with 11+ years of experience leading full-stack AI/ML development in startup and enterprise environments. I specialize in building and deploying large-scale NLP, LLM, and computer vision systems on cloud platforms (AWS, GCP, Azure) with modern DevOps practices (Docker, Kubernetes, CI/CD). I have a proven track record of driving product vision and scalability, including spearheading AI initiatives in healthcare to deliver secure, HIPAA-compliant solutions.\n\nI focus on LLM orchestration and multi-agent architectures using LangChain and LangGraph, translating complex requirements into technical architectures, mentoring engineering teams, and delivering high-impact AI products end-to-end. My work spans secure data pipelines, retrieval-augmented generation, and autonomous tool-enabled agent coordination, with a strong emphasis on production-readiness and measurable impact.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

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Expert

Intermediate

C++

Intermediate

Language

English

Fluent

Work Experience

Senior Software Engineer at Future Mind Labs, LLC

January 1, 2023 - Present

Led the architecture and implementation of Cognify, an LLM-powered custom query system integrating OpenAI GPT-4 to translate natural language into GraphQL queries, significantly reducing development time and errors. Developed retrieval pipelines with PGVector and Haystack for RAG, achieving sub-second latencies and high query relevance. Designed FuAssistX, a multi-tool AI assistant using FastAPI microservices, Model Context Protocol, and a LangGraph-based multi-agent architecture to improve modularity and reliability. Engineered containerized backend microservices and Kubernetes deployments ensuring 99.9% uptime during heavy load, delivering seamless chat interactions with sub-300ms response times.

Senior Machine Learning Engineer at Integral Ad Science

December 31, 2022 - August 27, 2025

Led development of scalable NLP data pipelines on Databricks, enhancing webpage classification, sentiment analysis, and entity recognition. Fine-tuned transformer-based NLP models on AWS to improve content relevance prediction and ad click-through rate by 15%. Managed end-to-end ML workflow reproducibility with MLflow and Databricks notebooks. Deployed FastAPI microservices with Redis caching and PostgreSQL for real-time ad serving, maintaining sub-100ms inference latency under dynamic loads. Collaborated cross-functionally to integrate NLP context signals into ad-serving pipelines, improving campaign ROI and model monitoring with AWS CloudWatch.

Full Stack AI Engineer at MediHealth AI, Inc

August 31, 2021 - August 27, 2025

Ensured HIPAA-compliant AI development and data pipelines. Built TensorFlow CNN-based computer vision models for medical imaging with ~90% accuracy. Developed NLP workflows using BERT transformers to extract insights from clinical records, aiding patient risk stratification. Created full-stack dashboards with React.js and Node.js/Flask integrating AI predictions and real-time visualizations. Managed secure cloud deployments on AWS and Azure with containerization and CI/CD pipelines. Worked closely with clinicians to validate AI solutions ensuring compliance with healthcare standards.

AI/ML Engineer at GlobalTech Corp

March 31, 2020 - August 27, 2025

Developed predictive ML models for image and signal data with over 90% accuracy. Built RESTful APIs and React front-ends for serving models and visualizing data. Automated data preprocessing and feature engineering pipelines for large-scale datasets. Maintained DevOps pipelines using Docker and Jenkins, and monitored services with Prometheus and Grafana. Researched advanced AI techniques including GANs and transfer learning to improve model robustness and support innovation roadmap.

Machine Learning Engineer at Becton, Dickinson and Company

July 31, 2018 - August 27, 2025

Designed CNN-based medical device diagnostic models achieving high accuracy on clinical imagery. Implemented YOLO-based real-time object detection to reduce manual review time by 20%. Developed NLP pipelines using NLTK and spaCy to automate feature extraction from clinical reports. Architected cloud data infrastructure on GCP with BigQuery, Cloud Functions, and Vertex AI for scalable training and deployment of AI solutions.

Machine Learning Intern at Houston Mechatronics

February 29, 2016 - August 27, 2025

Developed image analysis prototypes for diagnostic devices using ImageJ, MATLAB, and TensorFlow CNNs. Automated data processing in Python for accelerated experimental analysis. Collaborated on model refinement to improve prediction accuracy and documented results.

Senior Software Engineer at Future Mind Labs, LLC

January 1, 2023 - Present

Architected and developed Cognify, an LLM-powered query system integrating GPT-4 and PGVector for efficient data retrieval with low latency. Designed FuAssistX, a multi-tool AI assistant employing GPT-4 and MCP multi-agent architecture to invoke external services dynamically. Led full-stack infrastructure development using FastAPI, gRPC, Docker, and Kubernetes, ensuring high scalability and reliability with 99.9% uptime. Enhanced user experience with integrated conversational UI enabling sub-300ms response times and extensive domain knowledge coverage through hybrid knowledge retrieval pipelines.

Senior Machine Learning Engineer at Integral Ad Science

December 31, 2022 - September 4, 2025

Led scalable NLP data pipeline development and transformer-based model fine-tuning for content relevance on AWS, boosting classification accuracy and ad click-through rates. Deployed FastAPI microservices with Redis caching and PostgreSQL for real-time ad serving under stringent latency requirements. Collaborated cross-functionally to embed NLP signals into ad pipelines, tracked performance via CloudWatch, and maintained model accuracy above 90% during dynamic loads.

Full Stack AI Engineer at MediHealth AI, Inc

August 31, 2021 - September 4, 2025

Developed HIPAA-compliant computer vision and NLP models for medical imaging analysis and clinical note insights, improving diagnostic and patient risk stratification workflows. Built full-stack applications incorporating AI predictions with real-time visualizations. Managed cloud deployments on AWS and Azure using secure containerized environments with continuous integration pipelines. Collaborated closely with clinicians to ensure healthcare standards and actionable AI outputs.

AI/ML Engineer at GlobalTech Corp

March 31, 2020 - September 4, 2025

Created predictive ML models for image and signal data with over 90% accuracy. Developed REST APIs and web interfaces for serving AI insights. Automated data preprocessing and engineered features for large datasets. Maintained DevOps pipelines and production monitoring to ensure AI service reliability. Researched advanced AI techniques to improve model robustness and support innovation initiatives.

Machine Learning Engineer at Becton, Dickinson and Company

July 31, 2018 - September 4, 2025

Designed deep learning models for medical device diagnostics, implementing CNNs and real-time object detection with YOLO to reduce manual review times. Developed NLP pipelines to automate clinical report analysis. Built a cloud data pipeline on GCP for scalable model training and deployment, harnessing BigQuery, Cloud Functions, and Kubernetes Engine.

Machine Learning Intern at Houston Mechatronics

February 28, 2016 - September 4, 2025

Developed image analysis prototypes for diagnostic devices using ImageJ and MATLAB. Applied principal component analysis and CNN models for sample classification. Automated data processing with Python, reducing preparation time and improving iteration speed. Documented results and collaborated with senior engineers to refine model accuracy.

Senior Software Engineer at Future Mind Labs, LLC

January 1, 2023 - Present

Led Cognify: LLM-powered query interface using FastAPI and GraphQL; integrated GPT-4 to translate NL prompts to GraphQL; built retrieval using PGVector and Haystack; deployed on Kubernetes with auto-scaling; achieved sub-second latency and high uptime. Architected FuAssistX: multi-tool AI assistant with MCP tools, gRPC, and LangGraph-based coordination; implemented hybrid retrieval leveraging Haystack and vector embeddings to power accurate, context-rich answers.

Senior Machine Learning Engineer at Integral Ad Science

December 31, 2022 - September 25, 2025

Led scalable NLP data pipelines (tokenization, lemmatization) on Databricks for AdContext NLP Optimizer; developed transformer-based NLP models (BERT embeddings) on AWS to improve content relevance and CTR; used MLflow for experiment tracking; deployed FastAPI microservices on AWS ECS/EKS with Redis and PostgreSQL; achieved sub-100ms inference latency and high throughput; monitored production with CloudWatch and dashboards.

Full Stack AI Engineer at MediHealth AI, Inc

August 1, 2021 - September 25, 2025

Ensured HIPAA compliance with encrypted data pipelines and secure storage for PHI; developed computer vision models for medical imaging; built NLP workflows with BERT-based transformers; created full-stack dashboards (React/Node.js/Flask) for patient monitoring; deployed AI services on AWS and Azure with secure VPCs; containerized with Docker/Kubernetes; implemented GitLab CI/CD and collaborated with clinicians to validate model outputs.

AI/ML Engineer at GlobalTech Corp

March 31, 2020 - September 25, 2025

Developed predictive ML models (scikit-learn, TensorFlow) for image and signal data; created REST APIs and dashboards to present AI-driven insights; automated data preprocessing and feature engineering; maintained DevOps pipelines with Docker and Jenkins; monitored with Prometheus/Grafana; explored GANs and transfer learning to enhance model robustness.

Machine Learning Engineer at Becton, Dickinson and Company

July 31, 2018 - September 25, 2025

Designed deep learning models for medical device diagnostics; CNN-based classification for clinical imagery; real-time object detection with YOLO; NLP pipelines using NLTK and spaCy; built cloud-based data pipelines on GCP (BigQuery, Cloud Functions, GCS) and Vertex AI; deployed on Kubernetes Engine; developed scalable AI solutions for production use.

Machine Learning Intern at Houston Mechatronics

February 29, 2016 - September 25, 2025

Developed image analysis prototypes for diagnostic devices; used ImageJ and MATLAB for preprocessing; implemented PCA for feature extraction and prototype CNNs; automated data processing tasks in Python to accelerate experiments.

Senior Software Engineer at Future Mind Labs, LLC

January 1, 2023 - Present

Led Cognify, an LLM-powered data-query system, architecting FastAPI microservices and GraphQL API; integrated OpenAI GPT-4 to translate natural-language prompts into precise queries, reducing development time and syntax errors. Built a retrieval pipeline with PGVector embeddings and Haystack for retrieval-augmented generation, achieving sub-second latency and high query relevance. Integrated LibreChat into the GraphQL Explorer for in-situ query formulation and result visualization. Containerized services and used gRPC for inter-service communication, deployed on Kubernetes with auto-scaling to sustain thousands of concurrent sessions with 99.9% uptime. Designed FuAssistX, a multi-tool AI assistant using MCP and dynamic tool invocation, enabling robust, domain-specific workflows.

Senior Machine Learning Engineer at Integral Ad Science

December 1, 2022 - September 25, 2025

Led design and implementation of scalable NLP data pipelines on Databricks for the AdContext NLP Optimizer (tokenization, lemmatization, classification, sentiment analysis, named entity recognition) and integrated NLP-derived context signals into ad-serving pipelines. Developed and fine-tuned transformer-based NLP models (BERT embeddings) on AWS (EC2/SageMaker) to boost content relevance and CTR. Used MLflow for experiment tracking and Databricks notebooks for end-to-end ML workflows from data ingestion through model versioning. Deployed production FastAPI microservices (Docker) on AWS ECS/EKS with Redis caching and PostgreSQL to achieve sub-100ms inference latency. Monitored production metrics with CloudWatch and dashboards; retrained models to maintain >90% accuracy under dynamic load.

Full Stack AI Engineer at MediHealth AI, Inc

August 1, 2021 - September 25, 2025

Ensured HIPAA compliance by implementing encrypted data pipelines and secure PHI storage. Developed computer vision models (TensorFlow CNNs) to analyze medical imaging with ~90% accuracy. Built NLP workflows with BERT-based transformers to extract insights from EHRs and clinical notes. Created full-stack applications (React front-end, Node.js/Flask back-end) for patient monitoring dashboards integrating AI predictions and real-time visualizations. Deployed AI services on AWS and Azure with secure VPCs and automated scaling. Established containerized environments (Docker, Kubernetes) and GitLab CI pipelines for reliable production deployments, in collaboration with clinicians to ensure medical protocol compliance.

AI/ML Engineer at GlobalTech Corp

March 1, 2020 - September 25, 2025

Developed predictive ML models (scikit-learn, TensorFlow/Keras) for image and signal data with high classification accuracy. Created RESTful APIs (Flask/Django) and React-based front-ends to serve ML models and present interactive visualizations. Automated data preprocessing and feature engineering pipelines for large-scale datasets; improved model robustness through experimentation with GANs and transfer learning. Maintained DevOps pipelines (Docker, Jenkins) and monitoring (Prometheus/Grafana) to support high-uptime production AI services.

Machine Learning Engineer at Becton, Dickinson and Company

July 1, 2018 - September 25, 2025

Designed CNN-based image classification models for medical device diagnostics and implemented real-time object detection using YOLO to identify instrument issues, reducing manual review time. Built NLP pipelines to analyze clinical reports with NLTK and spaCy. Architected cloud-based data pipelines on GCP (BigQuery, Cloud Functions, Google Cloud Storage) and deployed ML workflows on Vertex AI and Kubernetes Engine, enabling scalable model training and reliable production deployment.

Machine Learning Intern at Houston Mechatronics

February 1, 2016 - September 25, 2025

Developed image analysis and ML prototypes for diagnostic devices. Used ImageJ and MATLAB for preprocessing/segmentation, applied PCA for feature extraction, and implemented prototype CNNs (TensorFlow/Keras). Automated data processing tasks in Python and documented results to support senior engineers.