Senior AI Engineer LLMOps And MLOps - Remote / Telecommute

• Lead the development and operations of AI and machine learning systems by building scalable, secure, and automated infrastructure across multi-cloud environments.
• Drive the production lifecycle of LLM applications, RAG pipelines, and ML models while ensuring performance, observability, and compliance.

Requirement/Must Have:

• Strong experience in MLOps or LLMOps in production environments.
• Hands-on expertise with AWS and Azure AI services.
• Proficiency in Python, SQL, and data engineering frameworks.
• Experience with CI/CD pipelines, containerization, and orchestration tools.
• Knowledge of model evaluation, monitoring, and observability frameworks.

Responsibilities:

• Build and maintain CI/CD and continuous training pipelines across AWS and Azure platforms.
• Design and implement LLMOps frameworks including RAG pipelines and vector database management.
• Develop data pipelines to integrate legacy systems with cloud-based ML workflows.
• Implement automated model evaluation frameworks for LLMs and traditional ML models.
• Deploy monitoring solutions for model performance, drift, latency, and cost management.
• Manage infrastructure using Infrastructure as Code tools.
• Collaborate with analytics platforms to ensure seamless data integration.
• Work with IT and security teams to manage networking and access controls.
• Optimize model serving for scalability and performance using containerization and serverless solutions.
• Establish version control for prompts, models, and datasets.
• Support data science workflows by automating feature engineering and deployment processes.
• Implement security controls to prevent vulnerabilities and ensure compliance.

Skills:

• AWS services including SageMaker and Bedrock.
• Azure AI services and cloud ecosystem.
• Python, SQL, and PySpark.
• Containerization using Docker and Kubernetes.
• Orchestration tools such as Airflow, Kubeflow, or Step Functions.
• Vector databases such as OpenSearch, Pinecone, or Azure AI Search.
• Model evaluation frameworks and observability tools.
• Infrastructure as Code tools such as Terraform or CloudFormation.
• Strong analytical and problem-solving skills.
• Excellent communication and collaboration skills.

Qualification And Education:

• Bachelor s degree in Computer Science or related field required.
• Master s degree in a quantitative discipline preferred.

Experience:

• 6+ years of engineering experience.
• Minimum 3+ years of experience in MLOps or LLMOps in production environments.
• Experience working in multi-cloud environments preferred.
• Experience collaborating with data science and enterprise IT teams preferred.