Senior AI/ML Architect for Secure Cloud Systems

Fidelity Investments Inc.; North Carolina; On-site; USD 180,000 - 240,000; Full time

Job summary

Fidelity Investments is seeking a Principal AI/ML Engineer to design and deploy advanced ML systems across enterprise platforms. You will lead secure model development, governance, and scalable cloud infrastructure leveraging SageMaker, Kubernetes, and IaC tooling.

Responsibilities include building robust ML pipelines, monitoring, and collaborative work with cybersecurity, data science, and cloud engineering teams to ensure trustworthy AI with high assurance and compliance.

Qualifications

• Bachelor's or Master’s degree in a relevant field with multiple years of ML platform experience.
• Experience designing secure, scalable ML systems for cloud environments.
• Strong knowledge of IAM, encryption, and governance in AI deployments.

Responsibilities

• Architects and implements AI/ML systems for training, inference, observability, and monitoring across distributed cloud environments.
• Develops secure AI frameworks and governance mechanisms to ensure transparency and risk mitigation.
• Builds agentic AI workflows automating data pipelines and model lifecycle operations.
• Prototyping advanced AI methodologies including federated learning and multi-agent safety.
• Evaluate performance and robustness of AI systems under high-throughput and adversarial conditions.
• Collaborate with cybersecurity, cloud engineering and data science teams to integrate AI safety into enterprise architecture.
• Mentor engineering teams on ML algorithms, security, and best practices in development.
• Provide technical guidance and oversee secure development patterns and infra designs.

Education

Bachelor's degree in Computer Science or related field

Master's degree in Computer Science or related field

Tools

Terraform

AWS

Azure

GCP

Kubernetes

Kubeflow

Airflow

MLflow

Job description

Fidelity Investments is seeking a Principal AI/ML Engineer to design and deploy advanced ML systems across enterprise platforms. You will lead secure model development, governance, and scalable cloud infrastructure leveraging SageMaker, Kubernetes, and IaC tooling.

Responsibilities include building robust ML pipelines, monitoring, and collaborative work with cybersecurity, data science, and cloud engineering teams to ensure trustworthy AI with high assurance and compliance.