Senior Devsecops Engineer

Position Summary:

We are seeking a Lead DevSecOps Engineer with deep expertise in cloud security, DevSecOps practices, and AI-enabled systems. As part of the team, you will help safeguard the security, privacy, and integrity of data and platforms that power machine learning and AI-driven solutions across analytics, benchmarking, data monetization, and reporting. The increased use of AI introduces unique security, privacy, and legal considerations, and this role plays a critical part in ensuring those risks are proactively managed through strong controls, policies, and tooling.

Key Responsibilities:
Lead the design and implementation of automated DevSecOps tooling that enables teams to deploy secure code rapidly and at scale.
Embed security throughout the software development lifecycle, including AI and ML workflows, with a focus on prevention, detection, and remediation.
Partner closely with software engineers to review and improve application code and infrastructure before production release.
Secure cloud-native architectures on AWS (must have), including EKS, RDS, and supporting services.
Design and maintain CI/CD pipelines with strong security guardrails, automation, and compliance controls.

Must Haves:
Strong AWS cloud experience (required), including hands-on work with EKS, RDS, and cloud-native security controls.
Proven experience in DevOps and DevSecOps environments with a heavy emphasis on automation.
Strong programming skills in Java, Python, Go, or other Object-Oriented Programming (OOP) languages.
Experience with microservices architectures, CI/CD pipelines, and infrastructure automation.
Hands-on experience with containerization and orchestration technologies such as Kubernetes.
Familiarity with CI/CD tools such as Jenkins or equivalent.

Plusses:
Experience securing AI and machine learning systems, including understanding risks related to data privacy, model security, and legal/regulatory compliance.
Knowledge of AI governance frameworks, security policies, and responsible AI practices.
Background as a full-stack engineer with a strong automation mindset.
Strong understanding of modern application and cloud security best practices beyond baseline terminology.