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I am a Principal AI/ML & Generative AI Engineer with 11+ years of experience building and scaling production-grade intelligent systems across healthcare, enterprise SaaS, and large-scale consumer platforms. I specialize in architecting and deploying LLMs, retrieval-augmented generation, and distributed ML on AWS and Azure, delivering measurable business outcomes and substantial workflow automation. I thrive on turning cutting-edge AI research into secure, compliant enterprise solutions, leading cross-functional teams through the full ML lifecycle—from data prep and model training to deployment, monitoring, and governance. My focus areas include MLOps, PHI/SOC2/HIPAA-aligned practices, and cost optimization, all aimed at accelerating time-to-value while maintaining reliability and security.…I am a Principal AI/ML & Generative AI Engineer with 11+ years of experience building and scaling production-grade intelligent systems across healthcare, enterprise SaaS, and large-scale consumer platforms. I specialize in architecting and deploying LLMs, retrieval-augmented generation, and distributed ML on AWS and Azure, delivering measurable business outcomes and substantial workflow automation. I thrive on turning cutting-edge AI research into secure, compliant enterprise solutions, leading cross-functional teams through the full ML lifecycle—from data prep and model training to deployment, monitoring, and governance. My focus areas include MLOps, PHI/SOC2/HIPAA-aligned practices, and cost optimization, all aimed at accelerating time-to-value while maintaining reliability and security.

Gabriel e N Cimato

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

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I am a Principal AI/ML & Generative AI Engineer with 11+ years of experience building and scaling production-grade intelligent systems across healthcare, enterprise SaaS, and large-scale consumer platforms. I specialize in architecting and deploying LLMs, retrieval-augmented generation, and distributed ML on AWS and Azure, delivering measurable business outcomes and substantial workflow automation. I thrive on turning cutting-edge AI research into secure, compliant enterprise solutions, leading cross-functional teams through the full ML lifecycle—from data prep and model training to deployment, monitoring, and governance. My focus areas include MLOps, PHI/SOC2/HIPAA-aligned practices, and cost optimization, all aimed at accelerating time-to-value while maintaining reliability and security.…I am a Principal AI/ML & Generative AI Engineer with 11+ years of experience building and scaling production-grade intelligent systems across healthcare, enterprise SaaS, and large-scale consumer platforms. I specialize in architecting and deploying LLMs, retrieval-augmented generation, and distributed ML on AWS and Azure, delivering measurable business outcomes and substantial workflow automation. I thrive on turning cutting-edge AI research into secure, compliant enterprise solutions, leading cross-functional teams through the full ML lifecycle—from data prep and model training to deployment, monitoring, and governance. My focus areas include MLOps, PHI/SOC2/HIPAA-aligned practices, and cost optimization, all aimed at accelerating time-to-value while maintaining reliability and security.

Available to hire

I am a Principal AI/ML & Generative AI Engineer with 11+ years of experience building and scaling production-grade intelligent systems across healthcare, enterprise SaaS, and large-scale consumer platforms. I specialize in architecting and deploying LLMs, retrieval-augmented generation, and distributed ML on AWS and Azure, delivering measurable business outcomes and substantial workflow automation.

I thrive on turning cutting-edge AI research into secure, compliant enterprise solutions, leading cross-functional teams through the full ML lifecycle—from data prep and model training to deployment, monitoring, and governance. My focus areas include MLOps, PHI/SOC2/HIPAA-aligned practices, and cost optimization, all aimed at accelerating time-to-value while maintaining reliability and security.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Language

English

Fluent

Work Experience

Lead AI/ML Engineer at SpringHealth

November 1, 2024 - Present

Led development of GenAI and LLM-based initiatives to automate claims review, prior authorization, and provider communication workflows. Built Python-based backend systems using FastAPI, async I/O, and REST APIs for secure, scalable integration between enterprise data services and LLMs. Designed and implemented multi-agent AI applications with Haystack, LangGraph, CrewAI, and AutoGen, enabling distributed reasoning and automated task delegation. Developed RAG-powered chatbots and virtual assistants using LangGraph, LlamaIndex, and GPT-4, improving clinical data retrieval and enterprise knowledge understanding. Created custom Python modules for prompt chaining, caching, and error handling, reducing model latency and API costs by ~30%. Integrated AI pipelines with Databricks, Azure ML, Azure Blob Storage, and Azure Functions for training, data preparation, and real-time inference. Established MLOps workflows using MLflow, Docker, and Azure DevOps, enabling reproducible experiments and au

Generative AI Engineer at McKesson

October 1, 2023 - August 31, 2024

Building NLP + LLM systems to extract insights from high-volume oncology data used in clinical research, pharma evidence generation, and care optimization. Designing RAG pipelines (LangChain, Pinecone, GPT) to improve clinical literature search, treatment evidence mapping, and precision data retrieval. Developing multi-model summarization agents that automate medical narratives and reduce physician documentation/analysis time. Deploying LLMs via Azure ML, Kubeflow, Kubernetes, supporting stable, secure, low-latency production inference at enterprise scale. Implementing prompt engineering frameworks + PHI compliant fine-tuning aligned with HIPAA / SOC2 / FDA AI guidance principles. Partnering with data engineering + oncology SMEs to convert unstructured biopsies, clinical notes, pathology records into structured features + model ready datasets.

Founding Software Engineer at Siena

February 1, 2023 - October 31, 2023

Design and develop full-stack agentic AI systems that autonomously manage customer experiences across commerce brands, unifying interactions, data, and workflows into a single intelligent layer to drive automation, CX excellence, and revenue growth. Led full-stack development of AI agents powering support, shopping, voice, and reviews. Enabled up to 80% automation and contributed to 4.9 CSAT and 88% resolution rates. Drove measurable revenue lift via AI-powered upsell, recovery, and personalized shopping agents. Designed RAG-based intelligence pipelines integrating vector databases, CRM, e-commerce, and real-time event streams. Built scalable backend services (Python, FastAPI, Node.js) deployed via Docker + Kubernetes with autoscaling and observability. Implemented LLM-driven reasoning, dynamic tool execution, and validation pipelines to ensure 99%+ action accuracy. Developed dashboards and analytics to track automation, resolution, CSAT, and revenue impact. Partnered with product, CX,

Generative AI Engineer at Ameritas

November 1, 2022 - December 31, 2023

Designed and implemented a fully serverless AWS architecture to automate paper-based insurance application processing from agents, licensed vendors, and customer portals. Built an event-driven ingestion pipeline using Amazon S3, AWS Lambda, and API Gateway to process scanned PDFs, images, and ZIP files at scale. Implemented Intelligent Document Processing (IDP) using OCR with LLM fallback via Amazon Bedrock Vision for accurate extraction from low-quality and complex documents.

AI/ML Engineer at AWS

May 1, 2019 - December 31, 2022

Architected and deployed production-grade machine learning systems for large-scale connected vehicle platforms supporting millions of users. Designed and implemented an end-to-end MLOps framework using Kubeflow, Kubernetes, and AWS EKS, reducing model deployment lifecycle from 1–2 weeks to 2–4 hours and enabling 8 data science teams to independently deploy and monitor models. Led development and production release of 4 ML-driven applications serving 4M+ connected vehicles, driving new subscription-based revenue streams. Developed and deployed predictive ML models achieving 85% accuracy in user behavior forecasting, enhancing personalization and improving experience for 1.2M+ active users. Re-engineered and optimized Driver Score algorithm and data pipelines, reducing daily data processing costs by 99% (from thousands to tens of dollars) through performance tuning and infrastructure optimization. Built a recommendation engine and analytics portal for a healthcare client, leveraging

Data Scientist at Facebook

October 1, 2017 - December 31, 2019

Conducted advanced analysis on large, complex datasets using statistical modeling and data mining techniques to generate actionable insights and data-driven business strategies. Designed and implemented scalable data pipelines using Python and SQL to power dashboards, reporting systems, audience segmentation models, and marketing performance analytics. Developed an operational analytics framework and customer journey mapping to optimize user onboarding flows and improve lower-funnel conversion rates. Built data-driven personalization strategies to increase brand awareness and sentiment for Facebook Gaming, driving creator loyalty and organic engagement through targeted campaigns and community growth initiatives. Led analytics initiatives supporting acquisition and re-engagement strategies for gaming video creators, leveraging behavioral data and performance metrics to improve retention and activation rates. Partnered with cross-functional stakeholders to define audience segmentation fo

Full Stack Developer at Mercury Development

October 1, 2015 - August 31, 2017

Led the full-stack development of 15+ custom web and mobile applications for clients ranging from startups to Fortune 500 companies. Architected scalable backend systems using Python (Django/Flask), Go and managed complex frontend deployments with React and Vue.js. Integrated various third-party APIs and payment gateways, ensuring robust data security and seamless user journeys across diverse product types.