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Mid-level generalist DevOps role, metro location, broad skillset attracts many qualified applicants.
Platform and cloud skills transfer across industries but require specific AWS and Kubernetes experience.
Explicit 3–5 year requirement plus mandatory AWS, Kubernetes, IaC, CI/CD, and database skills.
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Develop and ship platform-level features, shared services, frameworks, and SDKs for Workforce AI, supporting AI product teams.
Build and operate data integrations handling data flows between Workforce AI services and various systems including Cornerstone product data and AI/ML stores.
Implement end-to-end observability and production infrastructure on AWS (EKS/ECS), including CI/CD pipelines, monitoring (ELK/Splunk), incident triage, and database optimization.
3–5 years of relevant software/platform/infrastructure engineering experience.
Hands-on AWS production experience including EKS and/or ECS, IAM, VPC, S3, EC2, Lambda, RDS/DynamoDB.
Proficiency in at least two programming languages: Java, Python, Node.js with production code contributions.
Experience with CI/CD tools (Jenkins or equivalents), Infrastructure-as-Code (CloudFormation, Terraform, Helm), and operational monitoring tools (ELK or Splunk).
Engineer with strong experience in cloud platform development for AI/ML teams and real production infrastructure ownership.
Comfortable debugging production issues, triaging incidents rigorously, and writing blameless postmortems.
Experience tuning persistence layers for both relational and NoSQL databases and building scalable containerized workloads on AWS.