Design, build, and support AWS-based development and QA environments, with all development infrastructure provisioned and managed through Infrastructure as Code using Terraform, CloudFormation, or equivalent technologies.
Define reusable IaC modules, self-service provisioning patterns, configuration standards, and automated environment lifecycle controls.
Design and support Kubernetes platforms; develop, version, and govern reusable Helm charts for application configuration, packaging, deployment, upgrade, and rollback.
Lead the migration of legacy Jenkins workflows to GitHub Actions and build Harness-based deployment pipelines with automated testing, security controls, quality gates, release governance, and rollback capabilities.
Establish database DevOps practices using Liquibase, Flyway, or similar technologies; integrate versioned schema migrations, validation, and rollback controls into CI/CD pipelines.
Create and automate client QA environments, including legacy blueprints, representative test data, scheduled maintenance-release testing, and repeatable configuration.
Lead Jira and Confluence migrations and modernization, including content and space migration, permissions, integrations, governance, and engineering knowledge-management standards.
Migrate application artifacts and container images into enterprise Artifactory; establish package, dependency, versioning, and retention standards, including Conan where applicable.
Implement centralized logging, monitoring, alerting, and operational dashboards using Splunk and related technologies.
Enable AI-assisted engineering workflows, including automated defect routing, story and task support, and pipeline productivity improvements across repositories.
The successful candidate will bring 7+ years of experience in DevOps, Platform Engineering, Site Reliability Engineering, Cloud Engineering, or a comparable role, along with strong hands-on expertise across AWS, Kubernetes, Docker or containerization, Helm, and Infrastructure as Code. The role requires practical experience with Terraform and/or CloudFormation; enterprise CI/CD using GitHub Actions, Jenkins, and deployment automation; database migrations using Liquibase, Flyway, or similar technologies; and artifact repositories, container registries, package management, and observability platforms such as Artifactory and Splunk.
Experience with Harness, GitOps practices, Jira and Confluence migrations, Conan, AI-assisted software engineering, and financial services, capital markets, or post-trade processing platforms is highly valuable. Strong scripting, troubleshooting, communication, stakeholder management, and technical leadership skills are essential.
Fully automated, repeatable development and QA infrastructure managed through code.
Standardized Kubernetes deployments through governed Helm charts and reusable platform patterns.
Modern CI/CD pipelines with integrated application, database, testing, security, and rollback controls.
Successful Jira, Confluence, artifact repository, and delivery-tool migrations.
Improved observability, operational readiness, engineering productivity, and release reliability.
Design, build, and support AWS-based development and QA environments, with all development infrastructure provisioned and managed through Infrastructure as Code using Terraform, CloudFormation, or equivalent technologies.
Define reusable IaC modules, self-service provisioning patterns, configuration standards, and automated environment lifecycle controls.
Design and support Kubernetes platforms; develop, version, and govern reusable Helm charts for application configuration, packaging, deployment, upgrade, and rollback.
Lead the migration of legacy Jenkins workflows to GitHub Actions and build Harness-based deployment pipelines with automated testing, security controls, quality gates, release governance, and rollback capabilities.
Establish database DevOps practices using Liquibase, Flyway, or similar technologies; integrate versioned schema migrations, validation, and rollback controls into CI/CD pipelines.
Create and automate client QA environments, including legacy blueprints, representative test data, scheduled maintenance-release testing, and repeatable configuration.
Lead Jira and Confluence migrations and modernization, including content and space migration, permissions, integrations, governance, and engineering knowledge-management standards.
Migrate application artifacts and container images into enterprise Artifactory; establish package, dependency, versioning, and retention standards, including Conan where applicable.
Implement centralized logging, monitoring, alerting, and operational dashboards using Splunk and related technologies.
Enable AI-assisted engineering workflows, including automated defect routing, story and task support, and pipeline productivity improvements across repositories.
The successful candidate will bring 7+ years of experience in DevOps, Platform Engineering, Site Reliability Engineering, Cloud Engineering, or a comparable role, along with strong hands-on expertise across AWS, Kubernetes, Docker or containerization, Helm, and Infrastructure as Code. The role requires practical experience with Terraform and/or CloudFormation; enterprise CI/CD using GitHub Actions, Jenkins, and deployment automation; database migrations using Liquibase, Flyway, or similar technologies; and artifact repositories, container registries, package management, and observability platforms such as Artifactory and Splunk.
Experience with Harness, GitOps practices, Jira and Confluence migrations, Conan, AI-assisted software engineering, and financial services, capital markets, or post-trade processing platforms is highly valuable. Strong scripting, troubleshooting, communication, stakeholder management, and technical leadership skills are essential.
Fully automated, repeatable development and QA infrastructure managed through code.
Standardized Kubernetes deployments through governed Helm charts and reusable platform patterns.
Modern CI/CD pipelines with integrated application, database, testing, security, and rollback controls.
Successful Jira, Confluence, artifact repository, and delivery-tool migrations.
Improved observability, operational readiness, engineering productivity, and release reliability.
