Sentara Health is a leading integrated healthcare organization dedicated to improving health and well-being through innovative services, advanced medical practices, and compassionate care. With a strong commitment to community health, Sentara combines clinical excellence with cutting-edge technology to deliver comprehensive healthcare solutions. The organization values diversity, inclusion, and continuous learning, fostering an environment where employees can thrive professionally and personally. Recognized for its patient-centered approach and commitment to innovation, Sentara Health strives to set standards in healthcare delivery and medical research.

About The Role

Sentara Health is seeking a highly skilled and experienced Senior MLOps & Generative AI Engineer to join our expanding AI organization. This fully remote position offers an exciting opportunity to contribute to transformative healthcare initiatives by leveraging machine learning, deep learning, natural language processing, and Generative AI technologies. The ideal candidate will play a pivotal role in designing, deploying, and scaling enterprise-grade AI solutions that enhance healthcare outcomes and operational efficiencies. Collaborating closely with AI scientists, data engineers, software developers, and product teams, you will help operationalize AI/ML and Generative AI solutions at an enterprise level, ensuring they are secure, reliable, and compliant with healthcare regulations.

Qualifications

The ideal candidate will possess over 5 years of experience in building and deploying production software, machine learning systems, or AI platforms. A minimum of 1 year of hands-on experience with Generative AI or Large Language Model applications is required. Strong programming skills in Python, along with familiarity with deep learning frameworks such as PyTorch, Hugging Face Transformers, or TensorFlow, are essential. Experience with implementing Retrieval-Augmented Generation (RAG) architectures, vector search, embeddings, prompt engineering, and orchestration frameworks like LangChain or LlamaIndex is highly preferred. Candidates should have practical knowledge of vector databases such as Pinecone, Weaviate, or FAISS, and experience deploying AI solutions in cloud environments such as AWS, Azure, or GCP. A solid understanding of APIs, distributed systems, microservices, Kubernetes, and cloud-native infrastructure is necessary. Excellent communication skills and the ability to collaborate across technical and business teams are vital. A relevant degree or extensive experience in lieu of a degree is acceptable, with certifications not being mandatory.

Responsibilities

MLOps Engineering Responsibilities:

1. Design, develop, and maintain scalable machine learning infrastructure, pipelines, and automation tools supporting model training, deployment, monitoring, and lifecycle management.
2. Create and optimize CI/CD pipelines for AI workloads across development, staging, and production environments.
3. Build reusable platform capabilities, including feature stores, model registries, experimentation frameworks, and deployment automation.
4. Implement orchestration solutions for batch and real-time inference workloads, ensuring high availability and performance.
5. Develop monitoring systems to track model performance, detect drift, and ensure data quality and system reliability.
6. Collaborate with Data Scientists and Software Engineers to streamline the AI/ML lifecycle and improve operational efficiency.
7. Apply best practices in software engineering, including testing, security, observability, resiliency, and infrastructure-as-code.
8. Identify gaps within the ML platform ecosystem and architect scalable solutions to address them, supporting compliance and governance standards.
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Generative AI Engineering Responsibilities

1. Lead the architecture, design, and deployment of enterprise Generative AI solutions utilizing LLMs, foundation models, and agentic AI systems.
2. Design and implement RAG pipelines with vector databases, semantic search, reranking, and retrieval optimization strategies.
3. Build scalable LLM orchestration frameworks using tools like LangChain, LlamaIndex, or similar frameworks.
4. Develop advanced prompt engineering, chaining, and context management techniques to enhance LLM reliability and accuracy.
5. Evaluate and implement fine-tuning, parameter-efficient tuning, and prompt-based optimization for domain-specific applications.
6. Create evaluation frameworks to measure hallucination rates, response quality, bias, toxicity, latency, and business impact.
7. Implement AI safety measures, governance controls, and responsible AI practices tailored for healthcare environments.
8. Design scalable APIs and microservices supporting high-throughput AI applications within enterprise settings.
9. Optimize GenAI systems for cost, latency, throughput, and inference performance across cloud and hybrid environments.
10. Integrate healthcare data sources, knowledge repositories, and secure workflows to support enterprise GenAI solutions.
11. Research emerging GenAI technologies and frameworks, contributing to continuous innovation and improvement.
12. Develop technical documentation, roadmaps, and strategies for enterprise AI initiatives, ensuring alignment with organizational goals.
13. Collaborate with cybersecurity, compliance, and infrastructure teams to ensure secure deployment of GenAI solutions involving sensitive healthcare data.
14. Contribute to establishing AI platform standards, accelerators, templates, and best practices for scalable deployment.
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Benefits

Sentara Health offers a comprehensive benefits package designed to support your health, well-being, and professional growth. Employees have access to medical, dental, and vision plans to ensure comprehensive healthcare coverage. The organization provides reimbursement for adoption, fertility, and surrogacy expenses up to $10,000, supporting family-building efforts. Paid time off and sick leave policies promote work-life balance, alongside paid parental and family caregiver leave. Emergency backup care services are available to assist during unforeseen circumstances. Employees can benefit from long-term, short-term disability, and critical illness

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