Data Science AI Engineer

Summary Gainwell Technologies is seeking a highly skilled AI and GEN AI Engineer to design, develop, and deploy advanced AI and Generative AI (Gen AI) solutions, across our healthcare technology platforms. This role involves building and optimizing AI and GEN AI technologies, integrating them into existing systems, and ensuring their effectiveness in improving healthcare outcomes and operational efficiency while maintaining compliance with industry standards.

in our mission • Development based on AI/ GEN AI– Design, build, and train machine learning, deep learning, time series models, Gen AI (Multi modal LLMs), predictive analytics, Natural Language Processing, Image Processing solutions for healthcare applications. • Experienced in multiple LLM fine tuning techniques. • Experienced in building GEN AI solutions using RAG architecture. • Skilled in both Lang Chain and Lang Graph. • Experience in Agentic AI Frameworks and Workflow using Lang Chain, Lang Graph or Crew AI or Open AI Swarm. • Experienced in multiple Vector Databases as well as Graph Database • Skilled in Agentic AI Framework and has built at least one solution using Agentic AI. • End-to-End AI Solution Deployment – Develop, test, and deploy AI solutions in cloud and on-premises environments, ensuring reliability, scalability, and real-world impact. • Data Processing – Work with large healthcare datasets, performing data preprocessing, feature engineering, and model training while ensuring compliance with HIPAA and other regulatory standards. • System Integration – Skilled in API development and integrations. Implement and optimize AI models within Gain well’s existing technology stack, collaborating with software engineers to ensure seamless integration. • Experienced in ML Ops and LLM Ops. Experienced in evaluating models and continuous performance monitoring of both ML/DL and LLMs. Experienced in applying security measures in GEN AI solutions, implementing guard rails. • Performance Optimization – Continuously monitor, refine, and optimize AI / GEN AI models for accuracy, efficiency, and speed, leveraging ML Ops and LLM Ops best practices. • AI Research & Innovation – Stay updated with the latest AI/ML/ GEN AI advancements, exploring new technologies and methodologies to enhance solution effectiveness. • Compliance & Security – Ensure AI implementations adhere to healthcare industry regulations, ethical AI principles, and data privacy standards. • Automation & Workflow Enhancement – Identify opportunities to automate workflows and optimize business processes using AI-driven solutions. • Front End Development – Stream lit is a must.