Senior ML / Ops / Dev Ops Engineer, AI Health Cloud

BrightSpring Health Services

We are seeking a seasoned Senior MLOps / DevOps Engineer to lead the deployment, automation, and operationalization of AI/ML solutions within our next-generation AI-enabled Health Cloud Platform. This platform powers intelligent clinical and pharmacy applications using Generative AI, Agentic AI, Robotic Process Automation (RPA), and Retrieval-Augmented Generation (RAG) with domain-specific vector databases.

You'll work closely with AI architects, data scientists, and product teams to build scalable, secure, and compliant infrastructure that supports real-world healthcare workflows.

Design and implement robust MLOps pipelines for training, validation, deployment, and monitoring of AI/ML models.
• Automate infrastructure provisioning and CI/CD workflows across cloud environments (Azure, AWS, GCP).
• Manage containerization and orchestration using Docker, Kubernetes, and Helm.
• Optimize model serving and inference performance using tools like TorchServe, Triton, or FastAPI.
• Integrate RAG pipelines, vector databases (e.g., FAISS, Weaviate, Pinecone), and agentic frameworks (LangChain, AutoGen) into production environments.
• Ensure compliance with healthcare data standards (FHIR, HL7) and privacy regulations (HIPAA).
• Monitor system health, implement observability tools (Prometheus, Grafana), and respond to incidents.
• Collaborate with cross-functional teams to ensure scalability, reliability, and security of AI services.
• Mentor junior engineers and contribute to DevOps best practices across the organization.

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• 8+ years of experience in DevOps, MLOps, or cloud infrastructure engineering.
• Deep expertise in cloud platforms (Azure, AWS, GCP), containerization, and orchestration.
• Strong proficiency in Python and infrastructure-as-code tools (Terraform, Pulumi).
• Experience with ML lifecycle tools (MLflow, Kubeflow, SageMaker, Vertex AI).
• Experience with security, monitoring, and performance optimization in production environments.
• Familiarity with AI/ML frameworks (PyTorch, TensorFlow, Hugging Face Transformers).
• Knowledge of healthcare data formats and compliance standards (FHIR, HL7, HIPAA).
• Excellent problem-solving, collaboration, and communication skills.
• Travel up to 25%