{"id":2688529,"url":"https://alion.io/job/mphasis-senior-software-engineer-14","title":"Senior Software Engineer","company":{"id":59446,"name":"Mphasis","domain":"mphasis.com","url":"https://alion.io/company/mphasis","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Career site","truth_index":null},"role":"Backend","role_family":"Backend","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Taipei, Taiwan"],"countries":["TW"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":13000,"max_usd":39000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":6933},"experience_years_min":4,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"Azure DevOps","optional":false},{"name":"Bash","optional":false},{"name":"CI/CD","optional":false},{"name":"Docker","optional":false},{"name":"Git","optional":false},{"name":"GitHub Actions","optional":false},{"name":"Linux","optional":false},{"name":"Platform Engineering","optional":false},{"name":"Python","optional":false},{"name":"Terraform","optional":false},{"name":"VMWare","optional":false},{"name":"Amazon EKS","optional":true},{"name":"Azure","optional":true},{"name":"Kubernetes","optional":true}],"status":"live","first_seen_at":"2026-05-20T00:00:00Z","employer_posted_date":"2026-10-16","last_verified_at":"2026-10-16T17:15:01Z","board_verified":true,"closed_at":null,"days_open":149,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":149},"description":"We're evolving our platform toward AI-assisted and agent-driven engineering workflows, and we're looking for a DevOps Engineer to help shape this next chapter with us.\nYou'll work across both modern cloud-native systems and legacy operational environments, helping us modernize incrementally and pragmatically. The role offers broad exposure across infrastructure, automation, observability, CI/CD, and platform engineering domains.\nWhat You'll Do\nOperate and improve CI/CD pipelines across Azure DevOps and GitHub Actions.\nDesign, automate, and operate AWS infrastructure using Infrastructure as Code practices.\nMaintain and improve workloads running in our on-prem VMware environment as part of our hybrid platform footprint.\nHelp evolve our observability practice across infrastructure, services, workflows, and emerging AI-agent operations.\nContribute to AI-assisted and agent-driven automation workflows that improve both developer and operational efficiency.\nPartner with engineering teams to build paved-road developer experiences: self-service workflows, reliable tooling, and clear operational documentation.\nContinuously identify operational friction and improve reliability through automation and platform improvements.\nWho You Are\nOwnership mindset - you treat the platform as a product and proactively drive issues to resolution.\nPragmatic - you can navigate the gap between modern best practices and legacy operational realities.\nAutomation-first - if you've done it manually twice, you're already thinking about scripting it.\nCurious about AI-assisted engineering and developer workflows, not just as a user, but as someone interested in designing better systems around it.\nCollaborative and documentation-oriented by default.\nComfortable working across a broad range of infrastructure and platform engineering topics.\nThis role is ideal for engineers who enjoy shaping systems and workflows - not just operating them.\nMust Have\n4+ years of experience in DevOps, SRE, Platform Engineering, or related infrastructure roles.\nHands-on CI/CD experience with Azure DevOps Pipelines and/or GitHub Actions.\nSolid AWS production experience.\nPractical Terraform experience in production environments, including reusable modules and state management.\nProduction experience with Docker and containerized workloads.\nStrong scripting skills in Python and Bash.\nSolid Linux fundamentals and troubleshooting skills.\nPractical observability experience across metrics, logs, and traces - 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