{"id":1660494,"url":"https://alion.io/job/mastercard-principal-kubernetes-platform-engineer","title":"Principal Kubernetes Platform Engineer","company":{"id":252,"name":"Mastercard","domain":"mastercard.com","url":"https://alion.io/company/mastercard","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"A","score":94,"open_postings":221,"ghost_share":0.018,"stale_share":0.357,"repost_share":0.09,"time_to_fill_p50_days":21,"computed_at":"2026-10-10T05:45:15Z"}},"role":"DevOps","role_family":"DevOps","seniority":"lead","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Arlington, United States","New York, United States","United States","Georgia"],"countries":["US","GE"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":195000,"max":323000,"currency":"USD","period":"year","gross":null,"usd_annual":323000},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon CloudWatch","optional":false},{"name":"Amazon EKS","optional":false},{"name":"Amazon S3","optional":false},{"name":"Apache Kafka","optional":false},{"name":"ArgoCD","optional":false},{"name":"AWS","optional":false},{"name":"AWS CDK","optional":false},{"name":"Azure","optional":false},{"name":"Azure AKS","optional":false},{"name":"Bitbucket","optional":false},{"name":"C++","optional":false},{"name":"CI/CD","optional":false},{"name":"DNS","optional":false},{"name":"DynamoDB","optional":false},{"name":"External Secrets","optional":false},{"name":"GitHub","optional":false},{"name":"GitOps","optional":false},{"name":"Go","optional":false},{"name":"Grafana","optional":false},{"name":"Helm","optional":false},{"name":"Helmfile","optional":false},{"name":"IAM","optional":false},{"name":"Java","optional":false},{"name":"Jenkins","optional":false},{"name":"Kubernetes","optional":false},{"name":"Least Privilege","optional":false},{"name":"OpenTelemetry","optional":false},{"name":"PCI DSS","optional":false},{"name":"PostgreSQL","optional":false},{"name":"Prometheus","optional":false},{"name":"Redis","optional":false},{"name":"Rust","optional":false},{"name":"Amazon Aurora","optional":true},{"name":"Amazon SageMaker","optional":true},{"name":"AWS Bedrock","optional":true},{"name":"Flink","optional":true},{"name":"gRPC","optional":true},{"name":"MLFlow","optional":true},{"name":"Protobuf","optional":true},{"name":"TypeScript","optional":true}],"status":"live","first_seen_at":"2026-10-01T00:00:00Z","employer_posted_date":"2026-10-01","last_verified_at":"2026-10-10T23:17:25Z","board_verified":true,"closed_at":null,"days_open":10,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":10},"description":"Our Purpose\nMastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economywhere everyone can prosper. We support a wide range of digital payments choices, making transactions secure,simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential.\nTitle and Summary\nPrincipal Kubernetes Platform EngineerAbout MastercardMastercard is a global technology company in the payments industry. Our mission is to connect and power an inclusive, digital economy that benefits everyone, everywhere by making transactions safe, simple, smart, and accessible.\nUsing secure data and networks, partnerships, and passion, our innovations and solutions help individuals, financial institutions, governments, and businesses realize their greatest potential. With connections across more than 210 countries and territories, we are building a sustainable world that unlocks priceless possibilities for all.\nOverview\nAs a Principal Engineer within the Decision Stream program, you will combine enterprise-scale technical leadership with hands-on engineering for the next-generation Decision Management Platform. This is not a strategy-only role. You will actively design, code, prototype, and validate core platform capabilities, using modern AI-assisted development tools as part of day-to-day software engineering to move faster, improve quality, and help teams adopt better ways of building.\nKey areas of focus include leveraging disruptive technologies in real-time AI inferencing and decisioning to improve product effectiveness, increase business delivery, strengthen technical resilience, and lower cost of ownership. You will work closely with technology executives, senior leaders, and engineers to shape the overall AI & DPE technology strategy.\nRole\nOwn and operate the AWS EKS cluster, upgrades, node groups, managed add-ons, cluster logging, and capacity planning\nAuthor, maintain, and review Helm charts for application services, infrastructure (Kafka, Redis, PostgreSQL), and observability layers\nDesign and implement IAM/IRSA roles, KMS key policies, and Secrets Manager integration per workload, following least-privilege principles\nEnforce platform security standards, Pod Security Standards, Network Policies, container hardening, and PCI DSS 3.2.1 compliance gates in CI pipelines\nManage ECR image registry, scanning policies, base image governance, and lifecycle rules\nBuild and maintain AWS CDK infrastructure constructs for EKS, MSK, S3, RDS, DynamoDB, Secrets Manager, VPC, and supporting services\nDefine and operate ingress patterns, AWS ALB, ACM certificates, Route 53 DNS, and External Secrets Operator for secrets delivery\nLead platform security reviews and ensure all infrastructure changes are validated against organisational compliance standards before deployment\nCollaborate with application engineering teams across Rust, Go, Java, and C++ services to onboard workloads, review resource configurations, and resolve platform-level issues\nDrive GitOps delivery practices via ArgoCD, CI/CD pipeline integration, and feature branch release workflows\nDefine and document platform standards, runbooks, and onboarding guides for the engineering team\nAct as the platform SME, mentoring engineers, leading design discussions, and making architectural decisions for the AWS platform layer\nAll About You\nKubernetes - deep knowledge of node groups, OIDC provider, Pod Identity/IRSA, cluster autoscaler, and EKS upgrade operations\nHelm - multi-environment chart authoring, value layering strategies, Helmfile or ArgoCD-based GitOps delivery; experience converting AKS/Azure chart patterns to AWS EKS equivalents\nSecurity - IRSA design, KMS CMK policies, Secrets Manager, External Secrets Operator, Pod Security Standards, Network Policies, and PCI DSS compliance; experience operating under regulatory security standards\nNetworking - VPC design, private subnets, ALB ingress controller, ACM certificate management, Route 53, External-DNS, PrivateLink for internal AWS service endpoints, and security group design\nContainer Platform - ECR image registry management, image scanning, multi-stage Dockerfile practices, non-root container enforcement, read-only root filesystem, and supply chain security\nCI/CD & GitOps - Jenkins pipeline authoring, Bitbucket/GitHub pull request workflows, ArgoCD or Flux, feature branch strategies, and pre-push security gate enforcement\nObservability - CloudWatch Container Insights, AWS Distro for OpenTelemetry (ADOT), Prometheus, Grafana, and distributed tracing on EKS\nPreferred Qualifications\nAWS CDK (TypeScript) - authoring CDK L3 constructs and infrastructure-as-code best practices for EKS, MSK, RDS, DynamoDB, S3, and Secrets Manager\nKafka / Streaming - operating Kafka on Kubernetes, topic management, consumer group operations, and TLS/SASL authentication\nDatabase Operations - exposure to PostgreSQL (RDS/Aurora), DynamoDB, and Redis Enterprise in a Kubernetes or managed AWS environment\nApplication Background - familiarity with polyglot microservice environments (Rust, Go, Java/Flink, C++); ability to read and advise on Dockerfiles, gRPC/protobuf service contracts, and multi-language build pipelines\n• ML Platform Awareness - basic familiarity with SageMaker, Bedrock, or MLflow workloads running on EKS is a plusMastercard is a merit-based, inclusive, equal opportunity employer that considers applicants without regard to gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law. We hire the most qualified candidate for the role. In the US or Canada, if you require accommodations or assistance to complete the online application process or during the recruitment process, please contact  and identify the type of accommodation or assistance you are requesting. Do not include any medical or health information in this email. The Reasonable Accommodations team will respond to your email promptly.\nCorporate Security Responsibility\nAll activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must:\nAbide by Mastercard’s security policies and practices;\n\nEnsure the confidentiality and integrity of the information being accessed;\n\nReport any suspected information security violation or breach, and\n\nComplete all periodic mandatory security trainings in accordance with Mastercard’s guidelines.\n\nIn line with Mastercard’s total compensation philosophy and assuming that the job will be performed in the US, the successful candidate will be offered a competitive base salary and may be eligible for an annual bonus or commissions depending on the role. The base salary offered may vary depending on multiple factors, including but not limited to location, job-related knowledge, skills, and experience. Mastercard benefits for full time (and certain part time) employees generally include: insurance (including medical, prescription drug, dental, vision, disability, life insurance); flexible spending account and health savings account; paid leaves (including 16 weeks of new parent leave and up to 20 days of bereavement leave); 80 hours of Paid Sick and Safe Time, 25 days of vacation time and 5 personal days, pro-rated based on date of hire; 10 annual paid U.S. observed holidays; 401k with a best-in-class company match; deferred compensation for eligible roles; fitness reimbursement or on-site fitness facilities; eligibility for tuition reimbursement; and many more. Mastercard benefits for interns generally include: 56 hours of Paid Sick and Safe Time; jury duty leave; and on-site fitness facilities in some locations.THIS POSTING IS NOT FOR A CURRENT VACANCY, BUT MASTERCARD IS SEEKING RESUMES TO REVIEW IN THE FUTURE WHEN JOBS BECOME AVAILABLE.Pay Ranges\nArlington, Virginia: $195,000 - $323,000 USDRemote - Georgia: $170,000 - $281,000 USDRemote - Illinois: $170,000 - $281,000 USDRemote - Michigan: $170,000 - $281,000 USDRemote - Missouri: $170,000 - $281,000 USDRemote - New Jersey: $170,000 - $281,000 USDRemote - New York: $170,000 - $281,000 USDRemote - North Carolina: $170,000 - $281,000 USDRemote - Texas: $170,000 - $281,000 USDRemote - Virginia: $170,000 - $281,000 USDJob Posting Window\nPosting windows may change based on the volume of applications received and business necessity. 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