Senior DevOps Engineer
About the role
Foley is seeking a Senior DevOps Engineer to help modernize and scale the infrastructure that powers both our core compliance SaaS platform and our next generation of AI-enabled products. This role sits within the Infrastructure Platform team and will be responsible for evolving our Azure DevOps ecosystem, building GitHub Enterprise CI/CD foundations, advancing DevSecOps practices, and strengthening our cloud infrastructure through Infrastructure as Code.
This is a high-impact individual contributor role for an engineer who combines strong technical depth with ownership, automation-first thinking, and a passion for improving developer productivity, platform reliability, and security.
What you'll do
CI/CD Platform Modernization
Modernize and standardize Azure DevOps pipelines supporting Foley’s .NET SaaS platform, improving reliability, speed, and consistency.
Design and implement GitHub Enterprise and GitHub Actions workflows that establish scalable standards for AI-native products and engineering teams.
Drive pipeline-as-code adoption and enforce deployment best practices across development, staging, and production environments.
Integrate observability, automated quality gates, and testing frameworks directly into CI/CD workflows.
DevSecOps & Platform Security
Implement and manage SAST and DAST tooling across Azure DevOps and GitHub environments.
Establish security enforcement policies, vulnerability remediation workflows, and deployment gate standards.
Partner with engineering teams to improve application security posture through automation and secure development practices.
Maintain secure secrets management, IAM controls, and infrastructure security standards.
Cloud Infrastructure & Automation
Design, deploy, and maintain AWS infrastructure using Terraform and AWS CDK.
Develop reusable Infrastructure-as-Code patterns that support SaaS and AI platform workloads.
Improve platform reliability, scalability, and operational efficiency through automation and engineering best practices.
Contribute to architecture decisions that support long-term platform evolution and growth.
AI-Enabled Engineering
Leverage AI-assisted development tools to improve engineering productivity and operational excellence.
Support infrastructure requirements for AI workloads, agent platforms, model integrations, and emerging AI services.
Identify opportunities to automate repetitive operational work through AI and modern platform tooling.
Who you are
5+ years of experience in DevOps, Site Reliability Engineering (SRE), Platform Engineering, or related infrastructure roles.
Deep experience operating and supporting production workloads in AWS.
Hands-on expertise with GitHub Enterprise and GitHub Actions in enterprise-scale environments.
Strong Infrastructure as Code experience using Terraform and/or AWS CDK.
Experience building and maintaining Azure DevOps YAML pipelines.
Strong understanding of cloud security, IAM, secrets management, and least-privilege design principles.
Experience integrating SAST and DAST tooling into CI/CD pipelines.
Experience embedding automated testing (unit, integration, regression, and end-to-end testing) into deployment workflows.
Strong troubleshooting, automation, and systems-thinking skills.
Excellent written and verbal communication skills.
Nice to haves
Experience supporting .NET / C# application delivery pipelines.
Experience with Datadog or similar observability platforms.
Experience supporting AI/ML infrastructure, model-serving environments, vector databases, or agent-based platforms.
Familiarity with GitHub Advanced Security, Snyk, Semgrep, OWASP ZAP, or similar security tooling.
You Might Thrive in This Role If…
You enjoy solving complex infrastructure problems and improving engineering systems at scale.
You naturally look for opportunities to automate manual processes.
You balance speed with operational discipline and production reliability.
You proactively identify risks and drive solutions rather than waiting for direction.
You embrace new technologies, including AI-enabled engineering workflows, and apply them thoughtfully to improve outcomes.
This role is primarily remote (US-based) with occasional travel for team collaboration, training, and company events.
This role may be based remotely out of the following states: Arizona, California, Colorado, Connecticut, Florida, Georgia, Illinois, Indiana, Kansas, Maryland, Massachusetts, Michigan, Nebraska, New Hampshire, New Jersey, New York, North Carolina, Pennsylvania, Rhode Island, South Carolina, Tennessee, Texas, Virginia, and Wisconsin.