DevSecOps Platform Engineer
Ralliant- Location
- Rochester, NY, United States
- Workplace
- Hybrid
- Employment
- Full Time
- Salary
- —
Posted 1mo ago
DevSecOps Platform Engineer – Enterprise Analytics Services
Position Summary
The DevSecOps Platform Engineer enables the Enterprise Analytics Services product squads by designing, securing, automating, and operating the software delivery platform supporting a common code base across cloud-native and customer-managed on-premises deployments.
Build the Future of Enterprise Analytics
As part of Qualitrol's AI-Native Product Engineering organization, this role builds the engineering platform behind Specification-Driven Agentic SDLC, embedding security, automation, observability, and deployment portability into every release.
Mission
Own the engineering platform enabling CI/CD, Infrastructure as Code, DevSecOps, observability, hybrid-cloud deployment, and software supply-chain security across Enterprise Analytics Services.
Areas of Stewardship
- Design secure CI/CD pipelines using GitHub Actions and/or Azure DevOps.
- Automate deployments for Azure, Azure Arc, Azure Stack Hub, Kubernetes and customer-managed environments.
- Implement SAST, DAST, SBOMs, artifact signing, secrets management and vulnerability management.
- Develop Infrastructure as Code using Terraform, Bicep and Helm.
- Implement OpenTelemetry, Prometheus, Grafana and centralized logging.
- Partner with Product Engineers, Architects and QA to improve engineering productivity through AI-enabled automation.
What You'll Bring
- Bachelor's degree in Computer Science or related discipline.
- 5+ years in DevOps, Platform Engineering, SRE or DevSecOps.
- Kubernetes, Docker, Linux, Terraform, Helm, GitHub Actions/Azure DevOps, Python/Bash/PowerShell.
- Experience with Azure/AWS, Azure Arc, Azure Stack Hub and hybrid-cloud deployments.
- Knowledge of Zero Trust, IAM, OAuth2/OIDC, PKI, secure SDLC and industrial cybersecurity.
- Experience with Agile Scrum; SAFe 6.0 preferred.
- Experience using AI tools to automate engineering workflows.
Engineering Principles
- Automate before repeating.
- Security is a design requirement.
- Observability is a platform capability.
- Design once. Deploy anywhere.
- AI accelerates engineering; accountability remains human.
- Enable product teams through reusable platform capabilities.
Success Measures
- Automated secure pipelines adopted across all squads.
- Consistent cloud and on-prem deployments.
- Improved release velocity and software quality.
- Improved cybersecurity and compliance posture.
- High platform reliability and developer productivity.
Why Join Us
Build the engineering platform powering Qualitrol's next generation of enterprise analytics services and help shape an AI-Native Product Engineering organization.
#LI-PW1
Skills
- GitHub Actions
- Azure DevOps
- Azure
- Kubernetes
- SAST
- DAST
- Terraform
- Bicep
- Helm
- OpenTelemetry
- Prometheus
- Grafana
- Docker
- Linux
- Python
- Bash
- PowerShell
- AWS
- Zero Trust
- IAM
- OAuth 2.0
- OpenID Connect
- PKI
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