Senior AI Engineer

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Enable Data

WebsiteLinkedInAll Job Openings

51 - 200 employees

☁️ SaaS

⚕️ Healthcare Insurance

🏢 Enterprise

SaaS • Healthcare Insurance • Enterprise

Enable Data is a company that offers modern IT solutions to empower its customers by leveraging innovative data analytics and cloud platforms to drive increased value across their business ecosystem. They specialize in the implementation of large-scale SAS applications, distributed rules engines for processing health-related data, and managing data ingest frameworks. Enable Data serves industries requiring advanced data analytics and IT solutions, with a particular focus on healthcare quality and big data management.

📋 Description

• Design, build, and deploy end-to-end AI and machine learning solutions, with a focus on GenAI, NLP, and healthcare applications. • Develop and productionize LLM-based workflows, including prompt engineering, evaluation frameworks, fine-tuning approaches, and Retrieval-Augmented Generation systems. • Translate ambiguous business and healthcare problems into structured data science solutions with clear success metrics. • Own the full model lifecycle, including data preparation, experimentation, validation, documentation and articulation of results, deployment, monitoring, and continuous improvement following RAI guidelines. • Work with large-scale structured and unstructured data, including clinical, operational, claims, member, provider, or other healthcare-related datasets. • Partner with product, engineering, business, clinical, and compliance stakeholders to ensure solutions are scalable, explainable, secure, and aligned with business needs. • Lead, mentor, and develop a team of data scientists, and AI engineers, setting high standards for technical quality, analytical rigor, and delivery discipline. • Drive best practices in model development, code quality, documentation, reproducibility, and responsible AI.

🎯 Requirements

• 8+ years of experience in developing and implementing end-to-end solutions using Machine Learning and AI tools. • 5+ years of hands-on experience in NLP, deep learning, and transformer-based models. • 2+ years of practical experience building end-to-end Generative AI solutions, including LLM workflows, fine-tuning, evaluation, and RAG-based systems. • Strong proficiency in Python and PySpark is mandatory. • Proven experience building and deploying production-grade ML or AI systems at scale. • Strong business acumen with the ability to convert complex business problems into practical AI solutions that deliver measurable impact. • 2+ years of experience leading, mentoring, or managing high-performing data science teams is highly desirable. • Excellent written and verbal communication skills, with the ability to explain complex technical concepts to both technical and non-technical stakeholders. • Experience working in a matrix organization. • Experience in the healthcare domain is highly desirable, especially in areas such as clinical AI, payer/provider analytics, population health, claims, care management, medical operations, or health data platforms. • Experience working with healthcare data standards, privacy requirements, regulated environments, or responsible AI considerations in healthcare. • Hands-on experience with Azure, Databricks, or equivalent cloud and data platforms. • Working knowledge of MLOps, CI/CD for ML, model monitoring, model governance, and scalable deployment patterns. • Experience optimizing AI systems for accuracy, performance, latency, reliability, cost, and maintainability. • Exposure to multimodal AI, knowledge graphs, medical text analytics, or clinical decision support use cases is a plus.