Devsecops Engineer

Job Title: DevSecOps Engineer – MLOps & AI Fraud Detection

Location: U.S.

Overview:

We are seeking a DevSecOps Engineer with strong MLOps expertise to support real-time AI/ML fraud detection systems within a Financial Services environment. This role sits at the intersection of security, infrastructure, and machine learning, ensuring the scalability and security of production-grade AI platforms used to prevent financial fraud.

Key Responsibilities:

• DevSecOps & Platform Engineering: Design secure CI/CD pipelines and lead DevOps transformations toward automated, cloud-native delivery models.
• MLOps Enablement: Operationalize ML models for real-time fraud detection, managing deployment, monitoring, retraining, and data lineage.
• Infrastructure & Automation: Implement Infrastructure as Code (IaC) to automate and scale secure compute environments for mission-critical platforms.
• Security & Compliance: Embed security controls and governance across cloud and container layers to meet strict financial regulatory and audit requirements.
• Cross-Functional Collaboration: Partner with data scientists and security teams to transition models from experimentation to high-volume production.

Qualifications:

• Experience: 5+ years in DevOps, DevSecOps, or Platform Engineering, specifically supporting production AI/ML systems.
• Technical Skills: Expert proficiency in IaC (Terraform/CloudFormation) and CI/CD automation (Git-based workflows).
• Tools: Hands-on experience with cloud platforms (AWS, Azure, or GCP), container orchestration (Kubernetes/Docker), and ML monitoring tools.
• Domain Expertise: Background in Financial Services (FSI), specifically real-time risk or transaction monitoring systems.

Education & Requirements:

• Bachelor’s degree in Computer Science, Engineering, or a related technical field.
• Must pass a comprehensive background check for regulated financial environments.