Senior Software Engineer I - AI/ML
As a Senior Software Engineer I at Aledade, we maintain, improve, and expand our web application and data pipelines. We're looking for engineers who know that writing new code is not always the solution to a problem, but when technological changes are needed they create secure, maintainable, performant, correct, scalable, and stable solutions to the complex and unique challenges in our corner of the healthcare industry. They embrace strategies that minimize risk, leaning towards observability, alerting, metrics, high test coverage, and frequent releases that incrementally build value. \n Primary Duties: Develop and implement scalable and performant solutions. Partner, as a peer, with Engineering Managers, Product Managers, and stakeholders throughout Aledade to develop and execute technical roadmaps using Agile processes. Mentor and coach more junior engineers including thorough pull request reviews for other developers and be receptive to critical feedback on your own work. Minimum Qualifications: BS/BTech (or higher) in Computer Science, Engineering or a related field. 4+ years experience as an engineer building full-stack web applications as part of a cross-functional team. 3+ years of experience working with SQL or other database querying language on large multi-table data sets. 2+ years of experience acting as a trusted technical decision-maker in a team setting, solving for short-term and long-term business value. 2+ years of experience coaching other engineers. Responsibilities: Improve AI/ML infrastructure for model development, training, and deployment, with a focus on large language models and other generative AI architectures. Design multi-year vision, shaping the direction of crucial generative AI areas - text generation, image synthesis, multimodal models, and personalized content creation. Architect systems to enhance the capabilities and relevance of AI models, making complex data sets more accessible and actionable. Design and implement prompt engineering strategies to effectively guide generative AI models. Work closely with Product Management, Practices, Sales, Customer Success, and other stakeholders to identify and prioritize applied AI use cases within the organization. Analyze product usage patterns and trends to make data-driven decisions and forecasts for generative AI applications. Maintain the security of protected patient health information and ensure compliance with relevant regulations in the context of AI. Contribute to the development of APIs and interfaces for integrating generative AI capabilities into existing healthcare systems and applications. \n