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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates extensive experience in DevOps and Site Reliability Engineering (SRE) with a strong focus on managing CI/CD pipelines and deploying AI/ML Ops solutions on Azure and GCP. Proficient in infrastructure automation, observability, and MLOps practices, ensuring best practices are followed in data platform governance.
Highest-signal resume keywords
DevOps/Site Reliability Engineering ExperienceCI/CD Pipeline ManagementAzure and GCP ProficiencyMLOps Practices for AI SolutionsInfrastructure Automation with Terraform and Ansible
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
DevOpsSite Reliability EngineeringCI/CDMLOpsInfrastructure AutomationPython DevelopmentDockerKubernetesDatabricks AdministrationObservability
Soft Skills
CommunicationCollaborationAnalytical SkillsProblem-Solving
Tools & Technologies
AzureGCPTerraformAnsibleGitHub ActionsAzure DevOpsJenkinsDynatraceLangSmithMLflow
Certifications & Qualifications
Azure CertificationGCP CertificationDatabricks CertificationMLOps Certification
Industry Keywords
AIAgentic AIGenerative AIData Lake OperationsCloud Platform Engineering
Tech Stack
Tools & technologiesAnsibleAzureCloudDockerGoogle Cloud PlatformJenkinsKubernetesPythonTerraform
About the role
Key responsibilities & impact- Work in DevOps and SRE within the Forge & AI team
- Manage CI/CD
- Deploy AI/ML Ops pipelines and agentic AI
- Work on Azure and GCP
- Govern the Databricks data platform and data lake operations
- Ensure SRE best practices are followed
- Design, implement, and optimize ML pipelines
- Develop prompts for generative and agentic AI solutions
- Collaborate with software engineers, data scientists, and product managers
- Report directly to the Director of SRE
Requirements
What you’ll need- 7+ years of DevOps/Site Reliability Engineering (SRE) experience
- 5+ years of hands-on experience with Azure and GCP
- Experience with infrastructure automation using Terraform and Ansible
- Development/scripting with Python
- 5+ years of experience building and managing CI/CD pipelines, such as GitHub Actions, Azure DevOps, and Jenkins
- 4+ years of experience with Docker and Kubernetes
- Experience as a senior DevOps, SRE, or MLOps engineer supporting Azure and GCP cloud, data, and AI platforms
- Bachelor's degree in computer science, Engineering, or a related field
- Experience with MLOps practices for LLMs, generative AI, and agentic AI
- Experience with observability and monitoring platforms such as Dynatrace and LangSmith
- Experience with MLOps tools such as MLflow, Kubeflow, Vertex AI, and Azure ML
- Experience with Databricks administration
- Contributions to open-source projects
- Relevant certifications in Azure, GCP, Databricks, MLOps, data lake technologies, or AI/agentic AI platforms
- Experience in one or more of MLOps, Agentic AI/LLM platforms, Databricks administration, data lake operations, or cloud platform engineering
- Strong communication, collaboration, analytical, and problem-solving skills
Benefits
Comp & perks- Employer-subsidized Medical, Dental, Vision, and Life Insurance
- Short-Term and Long-Term Disability
- 401(k) match
- Flexible Spending Accounts
- Health Savings Accounts
- Employee Assistance Program (EAP)
- Educational Assistance
- Parental Leave
- Paid Time Off for vacation, personal business, sick time, and parental leave
- 12 Paid Holidays
- Competitive salary
- Leading-edge work and opportunities to develop solutions alongside dedicated experts