Hybrid Cloud & AI Systems Engineer

at Managed Health Care Associates, Inc.

• Job title: Cloud & AI Systems Engineer
• Job type: Full Time
• Experience level: Mid level, Senior
• Salary: Not specified
• Degree requirement: Bachelor's Degree
• Tech skills: Azure, Cloud, Docker, Kubernetes, Python, Terraform, VMware
• Location requirements: Hybrid, Parsippany, United States

About the role

• Cloud & AI Systems Engineer designing and optimizing Azure cloud infrastructure for health care solutions provider. Collaborating with teams on AI/ML workloads and implementing security and compliance measures.

Responsibilities

• Lead the design, implementation, and continuous improvement of Microsoft Azure cloud technologies (IaaS, PaaS, SaaS)
• Develop Azure policies, ARM templates, Blueprints, and governance strategies
• Build and maintain secure, scalable, and cost-optimized infrastructure solutions
• Drive infrastructure automation and self-service provisioning through Infrastructure-as-Code (IaC), scripting, and DevOps pipelines
• Monitor system performance, troubleshoot incidents, and ensure high availability and disaster recovery readiness
• Collaborate in cross-functional teams (e.g., with Finance, Data Science, Software Engineering and Security) to design, deploy, and maintain secure and scalable AI/ML pipelines
• Support retrieval-augmented generation (RAG) pipelines by implementing and maintaining secure endpoints, network isolation, and proper access controls
• Manage API security, authentication, and token usage for AI and LLM-based services, ensuring visibility into utilization and cost tracking
• Deploy and monitor machine learning models and APIs using Azure ML, Azure OpenAI, and containerized inference solutions
• Support AI DevOps/MLOps automation using Bicep, Terraform, or MLflow to streamline model deployment, configuration, and lifecycle management
• Implement monitoring and observability using Azure Monitor, Application Insights, and related tools to track AI API performance, latency, and errors
• Assist in operationalizing AI workloads in Azure ML, OpenAI, or custom inference endpoints while ensuring security and compliance alignment
• Contribute to AI governance by helping define secure model lifecycle processes, role-based access controls, and compliance checkpoints across environments
• Implement and manage AI-specific security controls, such as prompt injection mitigation, data masking in training datasets, and LLM access policies
• Collaborate with security team to evaluate and secure AI model endpoints, ensuring compliance with HIPAA and SOC 2 for AI workloads
• Support the development and enforcement of cloud security policies and incident response plans
• Collaborate with the security team to investigate cyber threats and deploy AI-driven threat detection and response tools
• Ensure compliance with industry standards (e.g., HIPAA, SOC 2, HITRUST) in all cloud and AI implementations

Requirements

• Bachelor’s degree in Computer Science, Engineering, or a related field (or equivalent experience)
• 5–7 years of experience with Microsoft Azure cloud architecture and automation, including design, deployment, and optimization of cloud environments, with exposure to AI/ML production systems
• Proven ability to build and maintain AI-native pipelines, including data ingestion, embeddings, inference endpoints, and vector databases
• Hands-on experience with Python for automation, scripting, and AI integration
• Familiarity with LLM application frameworks (e.g., LangChain, Semantic Kernel) and MLOps platforms (e.g., Azure ML Pipelines, MLflow, Kubeflow)
• Strong understanding of data engineering fundamentals, model deployment workflows, and AI observability tools (e.g., Weights & Biases, Arize, PromptLayer)
• Proficiency with Infrastructure-as-Code (IaC) tools such as Terraform, ARM templates, or Bicep
• Expertise in containerization and orchestration technologies (e.g., Docker, Kubernetes) for AI and cloud workloads
• Solid knowledge of Active Directory, Windows Server OS, VMware, networking, and hybrid cloud environments
• Demonstrated experience implementing DevOps automation and CI/CD pipelines (e.g., Azure DevOps)
• Knowledge of cloud cost optimization tools and methodologies
• Experience working in Agile/Scrum environments
• Excellent problem-solving, troubleshooting, root cause analysis, and performance optimization skills
• Strong documentation, communication, and collaboration skills with a customer-centric mindset
• Ability to translate business requirements into secure, scalable, and cost-efficient technology solutions
• Curiosity and willingness to experiment with generative AI, automation, and emerging technologies
• Experience contributing to AI strategy, governance, or ethical AI initiatives is a plus

Benefits

• Comprehensive medical, dental, vision and prescription plans with FSA/HSA options individual and family options
• Teledoc access
• Fitness Reimbursement
• Commuter Benefit Plan
• Access to an Employee Assistance Program (EAP)
• Paid Time Off
• Day off for your birthday and a floating holiday
• Paid Parental Leave
• 401K with a match
• Employee Stock Purchase Plan
• Life Insurance, short-term & long-term disability insurance
• Access to financial and legal advisors
• Tuition Reimbursement
• E-learning programs
• Ongoing Team Trainings
• Paid volunteer time-off
• Donation matching