Jaan Jagnits

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AI Engineer & ML Engineer

Steadfast Media - Consulting

Feb 2024 - Current (2 years 5 months)

Worked closely with researchers to create a real-world application on RBC infrastructure and containerized the applications' components for migration to Kubernetes OpenShift.Implemented and fine-tuned Llama models as verification agents, developing novel techniques for cost-effective factuality assessment that maintained while reducing API costs.Prepared Conda recipes to build Conda packages for internal and third-party Python libraries. Implemented CI/CD pipelines for components using Jenkins and UrbanCode Deploy.Developed a standard build tool for building and deploying Conda packages and Docker images, which supports auto-versioning and can be used both locally and from Jenkins.Implemented a resilient data sync app that copies data from

AI Engineer and Developer

FlairsTech

Jan 2019 - Jul 2024 (5 years 7 months)

Designed and implemented agentic actions for a QA agent, significantly enhancing its retrieval-augmented generation (RAG) capabilities.Designed and implemented an AI-driven content processing system capable of functioning as scheduled tasks for periodic NLP processing and on-demand HTTP APIs for real-time interactions, ensuring flexibility and scalability.Developed and deployed an end-to-end custom categorization workflow enabling users to define and manage categorization tasks tailored to their specific needs, incorporating both front-end and back-end (web and AI) components.Designed and implemented a scalable content processing system using Azure Functions to periodically process user content through advanced NLP tasks.Developed and deplo

Data Scientist

Eleks

Jul 2016 - Jan 2019 (2 years 7 months)

Engineered large-scale graph data pipelines integrating claims, prescriptions, and diagnosis data to uncover hidden connections among patients, providers, and treatments, driving actionable insights for market expansion and drug strategy optimization.Developed and deployed graph-based analytical models (using GraphSAGE, FastRP, and node embeddings, etc) to identify key physician networks, patient clusters, and drug-disease relationships, enabling precise targeting and influence mapping.Built and automated advanced healthcare analytics pipelines to generate insights on epidemiology, drug utilization, diagnosis patterns, patient journeys, and treatment outcomes, empowering targeted, data-driven market strategies.Architected a multi-agent anal

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Back End Developer

Jelvix

Apr 2014 - Jul 2016 (2 years 4 months)

Designed a GraphQL API for a leading European fintech company using Python, Django, and Graphene.Discovered and fixed performance issues related to Celery and database operations. Built user notification modules.Developed PySpark ETL jobs for one of the largest financial institutions.Set up a project from scratch, from repository creation to Git hooks, CI/CD, and deployment.Created a REST API for managing datasets, developed using Python and FastAPI.Supported application deployment to Pivotal Cloud Foundry.Created unit and integration tests for PySpark ETL jobs and the FastAPI application.Conducted cross-team Python learning sessions for a group of 50 - 100 developers and analysts. Topics included core Python, clean code, and Git webhooks.T

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