{"id":203654,"url":"https://alion.io/job/intetics-1143-senior-devops-engineer","title":"1143 | Senior DevOps Engineer","company":{"id":4245,"name":"Intetics","domain":"intetics.com","url":"https://alion.io/company/intetics","size_band":"501-1000","is_staffing_agency":false,"employer_type":"services","is_intermediary":false,"listed_via":null,"ats_vendor":"Workable","truth_index":{"grade":"A","score":87,"open_postings":59,"ghost_share":0,"stale_share":0.492,"repost_share":0.017,"time_to_fill_p50_days":40,"computed_at":"2026-10-27T05:46:45Z"}},"role":"DevOps","role_family":"DevOps","seniority":"senior","employment_type":null,"work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Philippines"],"countries":["PH"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":14500,"max_usd":40000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":3508},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon CloudWatch","optional":false},{"name":"Ansible","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Bash","optional":false},{"name":"Bitbucket","optional":false},{"name":"CI/CD","optional":false},{"name":"CloudFormation","optional":false},{"name":"GCP","optional":false},{"name":"GitHub","optional":false},{"name":"GitLab","optional":false},{"name":"Grafana","optional":false},{"name":"Kubernetes","optional":false},{"name":"Linux","optional":false},{"name":"Loki","optional":false},{"name":"OpenShift","optional":false},{"name":"PowerShell","optional":false},{"name":"Prometheus","optional":false},{"name":"Python","optional":false},{"name":"Terraform","optional":false},{"name":"Anomaly Detection","optional":true}],"status":"closed","first_seen_at":"2026-09-18T16:52:01Z","employer_posted_date":"2026-09-18","last_verified_at":"2026-10-26T19:26:46Z","board_verified":false,"closed_at":"2026-10-26T19:26:46Z","days_open":38,"trust":{"level":"ok","repost_count":0,"flags":[],"days_open":37},"description":"Intetics Inc., a leading American technology company specializing in custom software application development, distributed professional teams creation, software product quality assessment, and “all-things-digital” solutions, is on the lookout for a Senior DevOps Engineer to join our team and provide exceptional customer support.\nAbout the project:\nThe project is a cybersecurity platform that consolidates vulnerability, threat, and asset data to help organizations identify, prioritize, and remediate critical security exposures. It integrates data from a wide range of security tools and provides centralized capabilities for risk-based vulnerability management, workflow automation, and scalable exposure management.\nWorking hours are in UTC+10 / UTC+11.\nWhat You Will Do\nMaintain Reliable, Secure, and AI-Assisted Production Operations\nKeep production systems highly available, secure, patched, and performant. Use AI-assisted tooling to accelerate troubleshooting, identify risks, analyze incidents, and improve operational response.\nBuild and Maintain Kubernetes, Cloud, and DevOps Infrastructure\nOwn and improve Kubernetes clusters, containerized workloads, Infrastructure as Code, CI/CD pipelines, and cloud infrastructure. Leverage AI-assisted development and automation tools to improve delivery speed, configuration quality, and operational consistency.\nBuild Observability and Automation That Reduces Toil\nImprove monitoring, alerting, logging, dashboards, and automated remediation to identify issues earlier and reduce repetitive operational work. Apply AI and intelligent automation to correlate signals, surface anomalies, assist with root-cause analysis, and automate common SRE workflows.\nRequirements\n8+ years of experience in Site Reliability Engineering, DevOps, Cloud Engineering, Infrastructure Engineering, or related field.\nStrong hands-on experience with cloud platforms, including AWS, GCP, Azure, and/or OpenShift (OCP).\nDeep experience with Kubernetes, containers, and production container orchestration.\nExperience building and maintaining highly available, scalable, and secure production infrastructure.\nStrong experience with Infrastructure as Code, preferably Terraform, and configuration/automation tools such as Ansible.\nStrong scripting and automation skills using Python, Bash, or similar languages.\nStrong understanding of Linux, networking, security, cloud architecture, and distributed systems.\nStrong experience with observability and monitoring platforms such as Prometheus, Grafana, Loki, CloudWatch, or equivalent tools.\nExperience with incident response, root-cause analysis, production troubleshooting, and reliability engineering practices.\nExperience using AI-assisted engineering tools to improve infrastructure automation, troubleshooting, documentation, code generation, or operational workflows.\nAbility to identify opportunities where AI and automation can reduce operational toil, improve signal detection, and accelerate incident investigation.\nExperience building and maintaining CI/CD pipelines using GitHub, GitLab, Bitbucket, or similar platforms.\nAbility to provide technical leadership, mentor engineers, and help drive a culture of automation, reliability, and continuous improvement.\nMinimal Requirements\nMinimum 8 years of experience in SRE, DevOps, Cloud Engineering, Infrastructure Engineering, or a related field.\nStrong hands-on experience with cloud providers like AWS, GCP, Azure, and OpenShift (OCP).\nStrong understanding of Linux, networking, security, cloud architecture, and distributed systems.\nStrong experience with Kubernetes, Infrastructure as Code (terraform, tofu, CloudFormation), and automation (Python, bash, PowerShell).\nProven experience supporting highly available production systems, including observability, incident response, troubleshooting, and reliability improvements.\nPreferred Qualifications\nExperience integrating LLMs or AI-enabled tools into engineering or operational workflows.\nFamiliarity with AI-assisted log analysis, anomaly detection, incident summarization, or root-cause investigation.\nExperience building internal automation or tooling that combines APIs, scripting, infrastructure data, and AI models.\nUnderstanding of how to use AI safely in production engineering environments, including data security, access controls, validation, and human review.\nBenefits\nPaid Time Off\nWork From Home\nTraining & 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