Sentara Health
Senior MLOps & Generative AI Engineer - Remote
Virginia Beach, VA · Senior · Full-time
Sponsorship not specified$91k-$152kDetected 1 hour ago
PythonDistributed SystemsVector DatabasesAWSGCPAzureCloud PlatformsKubernetesCI/CDMachine LearningDeep LearningTensorFlowPyTorchNLPLLMsRAGAgentic AIMLOpsAI OrchestrationA/B TestingComplianceHIPAAEpicResearch
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57Sponsors, lottery-bound
Cap-exempt (no lottery)0
Sponsors this role90
Entry-level history0
PERM / green-card track0
Lottery odds (Level III)83
Fits your clock70
Sponsors, but it's cap-subject — you still face the weighted lottery (~45% per draw at Level III). Good if you win; have a cap-exempt backup on your list.
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About the role
- This role combines two critical focus areas:
- Generative AI Engineering - designing, architecting, deploying, and optimizing secure, production-ready GenAI applications and platforms leveraging LLMs, RAG architectures, vector databases, prompt orchestration, and AI evaluation frameworks.
- Sentara is hiring a Senior MLOps & Generative AI Engineer!
Responsibilities
- Design, build, and maintain scalable ML infrastructure and pipelines supporting model training, deployment, monitoring, governance, and lifecycle management.
- Build reusable ML platform capabilities including feature stores, model registries, experimentation frameworks, artifact management, and deployment automation.
- Implement scalable orchestration and workflow solutions for batch and real-time ML inference workloads.
- Create robust monitoring systems to measure model performance, detect model drift, monitor data quality, and ensure production reliability.
- Develop automation tools and self-service capabilities to improve the efficiency, scalability, and reliability of MLOps processes.
- Collaborate with Data Scientists and Software Engineers to streamline the ML lifecycle from experimentation through enterprise production deployment.
- Support enterprise AI governance, compliance, auditability, and model risk management requirements.
- Lead the architecture, design, and deployment of enterprise Generative AI solutions leveraging LLMs, foundation models, and agentic AI systems.
- Design and implement Retrieval-Augmented Generation (RAG) pipelines using vector databases, embeddings, semantic search, reranking, and retrieval optimization strategies.
- Build scalable LLM orchestration frameworks using technologies such as LangChain, LlamaIndex, Semantic Kernel, or equivalent frameworks.
Requirements
- 5+ years of experience building and deploying production software, ML systems, or AI platforms.
- Strong programming skills in Python and experience with software engineering best practices.
- Hands-on experience implementing RAG architectures, vector search, embeddings, prompt engineering, and LLM orchestration frameworks.
- Experience with vector databases such as Pinecone, Weaviate, Chroma, FAISS, Milvus, or equivalent technologies.
- Experience deploying AI/ML systems in cloud environments including AWS, Azure, or GCP.
- Strong understanding of APIs, distributed systems, microservices, and scalable backend architectures.
- Experience with Kubernetes, containerization, orchestration, and cloud-native infrastructure.
- Experience implementing CI/CD pipelines, infrastructure automation, and MLOps best practices.
- Strong understanding of AI/ML lifecycle management, governance, model versioning, and production operations.
- Experience designing secure, scalable, production-ready AI platforms and services.
Nice to have
- Experience with AI governance frameworks, LLM evaluation methodologies, and AI safety tooling.
- Experience with GPU infrastructure optimization and scalable inference architectures.
- Familiarity with multi-agent AI systems and autonomous workflows.
- Experience with event-driven architectures, streaming pipelines, and real-time inference systems.
- Exposure to model fine-tuning techniques including LoRA, PEFT, RLHF, or domain adaptation strategies.
- Experience with enterprise AI platform architecture and internal developer platforms.
- Prior experience mentoring engineers and leading technical initiatives.
- 5+ years of relevant experience with a degree (Required)
Compensation
- We provide market-competitive compensation packages, inclusive of base pay, incentives, and benefits.
Benefits
- Medical, Dental, Vision plans
- Adoption, Fertility and Surrogacy Reimbursement up to $10,000
- Paid Time Off and Sick Leave
- Paid Parental & Family Caregiver Leave
- Long-Term, Short-Term Disability, and Critical Illness plans
- Life Insurance
- Tuition Assistance - $5,250/year and discounted educational opportunities through Guild Education
- Reimbursement for certifications and free access to complete CEUs and professional development
- Develop and optimize CI/CD pipelines for machine learning and AI workloads across development, staging, and production environments.
- Implement AI safety guardrails, governance controls, content filtering, and responsible AI practices for enterprise healthcare environments.
- Integrate enterprise data sources, healthcare systems, and knowledge repositories into secure GenAI workflows.
- Collaborate with cybersecurity, compliance, and infrastructure teams to ensure secure and compliant deployment of GenAI solutions involving PHI and sensitive healthcare data.
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This listing is sourced directly from Sentara Health's careers page and normalized into a canonical job model.