Devops/SRE/AI

Saicon Consultants Inc

  • Parsippany, NJ
  • 19 days ago
    Want to know if you’re a fit?
    Upload your resume and let our AI show you.

    Skills

    • Amazon Web Services (AWS)unmatched
    • Artificial Intelligence (AI)unmatched
    • Automationunmatched
    • Best Practicesunmatched
    • Cloud Applicationsunmatched
    • Cloud Computingunmatched
    • Computer Securityunmatched
    • Computer Systemsunmatched
    • Continuous Deployment/Deliveryunmatched
    • Continuous Integrationunmatched
    • DevOpsunmatched
    • Distributed Computingunmatched
    • Dockerunmatched
    • Ecosystemsunmatched
    • GCP (Good Clinical Practices)unmatched
    • GPU (Graphics Processing Unit)unmatched
    • GitHubunmatched
    • High Availabilityunmatched
    • Identify Issuesunmatched
    • Infrastructure Softwareunmatched
    • Jenkinsunmatched
    • Linux Administrationunmatched
    • Machine Learningunmatched
    • Machine Toolunmatched
    • Microsoft Windows Azureunmatched
    • Performance Tuning/Optimizationunmatched
    • Python Programming/Scripting Languageunmatched
    • Reliability Engineeringunmatched
    • Root Cause Analysisunmatched
    • Scalable System Developmentunmatched
    • Scripting (Scripting Languages)unmatched
    • Security Infrastructureunmatched
    • Software Development Lifecycle (SDLC)unmatched
    • Splunkunmatched
    • Vulnerability Scannersunmatched

    Description


    Job Description:
    We are seeking a highly skilled DevOps / Site Reliability Engineer (SRE) with experience supporting modern AI platforms and cloud-native infrastructure. This role will focus on building scalable, reliable infrastructure for AI workloads while partnering closely with security and engineering teams to operationalize findings from Mythos AI, an emerging AI-driven security platform used to identify code vulnerabilities and infrastructure risks.

    While prior hands-on experience with Mythos AI is not expected, candidates should understand its purpose within the AI security ecosystem and be comfortable implementing the remediation work it identifies.

    This position is ideal for an engineer who enjoys automating infrastructure, improving software delivery pipelines, and supporting the rapid adoption of AI technologies in enterprise environments.

    Responsibilities:

    • Design, build, and maintain highly available infrastructure supporting AI and machine learning platforms.
    • Develop scalable platform engineering solutions that enable reliable deployment and operation of AI services.
    • Partner with development and security teams to remediate vulnerabilities and infrastructure issues identified by Mythos AI.
    • Improve platform reliability through automation, monitoring, observability, and proactive performance tuning.
    • Build and maintain robust CI/CD pipelines for application and infrastructure deployments.
    • Automate operational workflows using Python and Infrastructure-as-Code practices.
    • Implement DevSecOps best practices throughout the software development lifecycle.
    • Support containerized workloads and cloud-native applications.
    • Troubleshoot production issues, perform root cause analysis, and implement long-term reliability improvements.
    • Optimize deployment strategies, release automation, and infrastructure scalability.
    • Collaborate with AI engineering teams to ensure AI services are secure, resilient, and production-ready.

    Required Qualifications:

    • 5+ years of experience in DevOps, Site Reliability Engineering, or Platform Engineering
    • Strong experience designing and maintaining CI/CD pipelines (GitHub Actions, GitLab CI, Jenkins, Azure DevOps, or similar)
    • Strong Python scripting and automation skills
    • Experience supporting cloud infrastructure (AWS, Azure, or GCP)
    • Experience with Infrastructure as Code (Terraform, CloudFormation, or Pulumi)
    • Hands-on experience with Docker and Kubernetes
    • Strong understanding of Linux systems administration
    • Experience implementing monitoring and observability solutions (Prometheus, Grafana, Datadog, Splunk, etc.)
    • Experience working with security scanning tools and vulnerability remediation
    • Familiarity with DevSecOps principles and secure software delivery

    Preferred Qualifications:

    • Experience supporting AI platform engineering or machine learning infrastructure
    • Understanding of AI model deployment, inference infrastructure, and scalability considerations
    • Familiarity with GPU-enabled infrastructure and AI compute environments
    • Knowledge of vector databases, LLM deployment, or MLOps concepts
    • Experience with Kubernetes operators, service mesh, or distributed systems
    • Exposure to AI security tooling such as Mythos AI or similar AI-assisted vulnerability management platforms
    • Experience integrating automated security scanning into CI/CD pipelines

    Numbers & Facts

    LocationParsippany, NJ

    Similar Jobs