Role Description Architect and maintain highly available, secure cloud infrastructure, primarily on AWS, GCP, Azure; - Lead CI/CD efforts by building and improving pipelines (GitHub Actions, GitLab CI, Jenkins, etc.); - Manage Kubernetes clusters in production, including Helm charts, auto-scaling, and service mesh; - Implement Infrastructure as Code (IaC) using Terraform, Pulumi, or similar tools; - Automate provisioning, configuration management, monitoring, and incident response; - Drive observability across systems with tools like Prometheus, Grafana, Loki, Datadog, or ELK; - Collaborate with software engineers to enable fast, safe, and repeatable deployments; - Mentor team members and establish DevOps best practices across the organization; - Ensure compliance and security through automation, policy-as-code, and secure pipeline management; - Use AI coding assistants (e.g., Claude Code, GitHub Copilot) to speed up automation scripting, IaC development, and troubleshooting; - Apply AIOps practices (anomaly detection, automated root-cause analysis) to improve incident response and operational efficiency. Qualifications - 5+ years of experience in DevOps, SRE, or Cloud Engineering roles; - Expertise with cloud platforms (AWS preferred; GCP or Azure also valuable); - Production experience with Kubernetes and containerized workloads; - Strong skills in scripting or programming (e.g., Python, Go, Bash); - Deep understanding of CI/CD, GitOps (Argo CD, Flux, or similar), and modern deployment strategies (blue/green, canary, etc.); - Hands-on experience with Terraform, Helm, and cloud networking concepts; - Working knowledge of policy-as-code (OPA, HashiCorp Sentinel, or similar); - Familiarity with monitoring, alerting, and incident management best practices; - Proven ability to work cross-functionally with engineering, security, and QA teams; - Strong communicator and mentor; able to guide and uplift other engineers; - Practical experience using AI-assisted development or ops tools (e.g., GitHub Copilot, Claude Code) in daily workflows. Requirements - Certifications such as AWS DevOps Engineer, CKA, or Terraform Associate; - Background in scaling SaaS or multi-tenant platforms; - Experience with secrets management (Vault, AWS Secrets Manager); - Experience building or integrating AIOps solutions (anomaly detection, automated root-cause analysis, predictive scaling). Company Description Softeq communicates only from @softeq.com email addresses. We never request payments or fees for any reason during hiring — including trainings or courses to be completed, equipment, onboarding, or background checks — and we will not ask for banking information, cryptocurrency or gift cards. If you receive a message from any other domain or requesting payment, do not respond and report it to abuse@softeq.com.

• Support and improve many hybrid production infrastructure environments for more than 15 development teams handling 100+ products, 10K+ domains and Billions of hits day. • Help developers solve complex technical problems for multiple stacks and environments. • Architect and plan improvements of a multi-datacenter development environment. • Participate in design decisions, including new technology research and prototyping. • Advocate and help development teams to migrate their services to more automated and elastic infrastructures leveraging best-of-breed technology (Cloud, Kubernetes, Serverless, etc.) • Documenting processes and monitoring performance metrics for all our environments and services. • Promote and implement proper CICD strategies and practices. • Help develop and ameliorate critical cloud-based shared services serving many Products. • Support and augment the coverage of our Infrastructure as Code (IaC) setup. • Mentoring junior DevOps in gaining experience and follow best practices.

Role Description We are hiring a DevOps Engineer to support and scale our Data and AI platform in production. This role focuses on building reliable infrastructure for data pipelines and ML systems, standardizing deployment patterns, and ensuring performance, observability, and cost efficiency across compute-intensive workloads. Responsibilities - Build and operate infrastructure for data pipelines and AI/ML workloads - Develop and maintain CI/CD for application and model lifecycle (build, train, deploy) - Manage Infrastructure as Code (Terraform) across environments - Support containerized workloads and orchestration (Docker, Kubernetes) - Partner with Machine Learning teams and engineering to productionize models - Implement monitoring, logging, and tracing for data flow and model performance - Improve reliability, scalability, and cost efficiency of data systems - Enforce security and access controls for data and infrastructure - Reduce operational overhead through automation and tooling Qualifications - 3+ years of experience in DevOps, SRE, or infrastructure engineering - End-to-End MLOps/LLMOps Expertise: Experience deploying and maintaining ML/AI workflows. Familiarity with the unique nature of promoting AI assets (models, datasets, and code) through the lifecycle. - Strong cloud experience (AWS preferred) - Proficiency with Terraform (or similar IaC tools) - Experience with Docker and Kubernetes - Familiarity with CI/CD and Git-based workflows - Experience supporting data platforms (e.g., Airflow, Kafka, Spark, or similar) - Programming/scripting (Python, Bash, or similar) - Experience with observability tools and practices Preferred Qualifications - Experience with MLOps tooling (e.g., MLflow, SageMaker, Kubeflow) - Familiarity with LLM-based systems and AI observability (token usage tracking, prompt versioning) and evaluation loops - Experience with real-time or high-throughput data systems - Exposure to security and compliance requirements (e.g., SOC 2, HIPAA) - Experience with specific MLOps tooling (Outerbounds, SageMaker, Metaflow) and vector database Benefits - Privatized Medical, Dental & Vision Coverage - Supplemental health and wellness benefit - Modern Health and Vivawell - Work From Home stipend - Flexible Time Off (FTO), wellbeing days, Summer Fridays, and Mid-Year and Year-End Reflect & Recharge (Company Holidays), Paid Holidays - Christmas Bonus (15-day aguinaldo) - Monthly meal/grocery voucher via Si Vale card - Catered Lunch - A relocation bonus for candidates joining us from a different city - Annual Bonus - Tuition Reimbursement - Saving Funds - Employee Resource Groups (ERGs)

• Operating and managing modern container platforms • Setting up and running production-grade Kubernetes environments • Version control and automation of deployments for complex infrastructures • Identifying and monitoring critical systems and CI/CD pipelines