11 publicaciones de empleo destacadas de reliability engineer en castelar buenos aires (¡Están contratando!)

Release Engineer
Medallia —Buenos Aires, Buenos Aires
- Tiempo completo
6h
Reporting Analyst
サイネオス・ヘルス —Buenos Aires, Buenos Aires
10d
Software Engineers (Backend .NET/C#)
Betsson Group —Buenos Aires, Buenos Aires
Postulación rápida
Cloud Architect
dLocal —Buenos Aires, Buenos Aires
- Tiempo completo
Postulación rápida
Reporting Analyst
Syneos Health Commercial Solutions —Buenos Aires, Buenos Aires
10d
Product Quality Analyst
Prysmian Group —Buenos Aires, Buenos Aires
Lead C# Software Architect
Marvik —Buenos Aires, Buenos Aires
Mobile Engineer (Remote)
Fireblocks —Buenos Aires, Buenos Aires
Postulación rápida
Engineering Technical Lead
Modus Digital —Capital Federal, Buenos Aires
- Tiempo completo
Postulación rápida
Software Engineer, Robotics
Scale AI —Buenos Aires, Buenos Aires
Senior Software Architect (100% Remote - Worldwide)
Tether Operations Limited —Buenos Aires, Buenos Aires
- Tiempo completo
2h

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Release Engineer

Medallia -
Buenos Aires, Buenos Aires

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Detalles del empleo

Tiempo completo
Hace 6 horas

Descripción completa del empleo

Overview:

The Engineering Operations team within Medallia Cloud Services is looking for a world-class Release Engineer to design, drive, and own the delivery of various Medallia platform and self-service products. You will not just be managing schedules; you will be treating our delivery pipeline as a product itself, building the internal tooling that empowers our engineering org to ship faster and more reliably.

The role includes the coordination and management of releases across various portfolios, but heavily indexes on helping product and project teams build automated solutions to deploy safely into production on a different cadences from daily to quarterly basis.

As the owner of the Release Management lifecycle, you will work collaboratively across the SDLC—partnering with Product Development, Test Engineering, SRE, and Managed Services. The ideal candidate is a former developer or automation fanatic who thrives in a high-growth environment. You are a strong leader who can communicate clearly to executive stakeholders, understand complex technical dependencies, and immediately spot opportunities to replace manual effort with code.

Responsibilities:

Responsibilities:

Work with Development engineers and leaders to understand impacts of branches and code merges.
Manage risk and resolve issues that affect release scope, schedule and quality.
Support cross-functional teams by identifying technical dependencies and building automated solutions to mitigate them.
Collaborate with stakeholders to identify and communicate technical bottlenecks or release blockers.
Continually work towards making improvements in the release process through automation.
Analyze and eliminate manual work or process gaps to optimize release efficiency.
Work improving CI/CD standards that optimize the Medallia SDLC
Utilize AI and programming skills (Python or Java) to build internal tools and automate manual processes to enhance release reliability and speed.

Qualifications:

Minimum Qualifications:

Bachelor's degree in Computer Science, Engineering or related field.
3+ years experience in a software development role (e.g., Software Engineer, Test Engineer, QA Engineer).
Understanding of CI/CD practices, including semantic versioning, quality gates, release processes, deployment automation
Experience working in release/DevOps environments with a strong focus on automation.
Proven ability to design and implement automated deployment pipelines.
In-depth knowledge of monitoring Kubernetes tools for tracking purposes on deployments.
Hands-on experience in Python or Java for infrastructure tooling and script automation.

Preferred Qualifications:

Solid grasp of CI/CD methodologies, spanning automated deployments, quality gates, and versioning standards.
Experience working with code management, continuous integration and tracking tooling (Git, Jenkins, Jira are desired).
Experience communicating (written and verbal) with technical and non-technical stakeholders across multiple organizations (including executive level).
Proficiency in AI/Machine Learning as a strong asset for optimizing release workflows and predictive deployment health monitoring.
Comfortable leveraging modern AI coding assistants to accelerate internal tool development.

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