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ScienceLogic

Platform Engineer- SDET, Kubernetes- Skylar AI Platform

Reposted One Month Ago
Remote or Hybrid
Hiring Remotely in India
Mid level
Remote or Hybrid
Hiring Remotely in India
Mid level
Build and maintain lab environments and CI/CD pipelines for the Skylar AI platform. Create automated end-to-end tests, simulate user journeys and telemetry, validate integrations and performance, manage versioning and rollback tests, support data generation, and document environments. Partner with product, data science, QA, and engineering to ensure reliable monthly updates and platform availability.
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About ScienceLogic…

ScienceLogic is redefining IT operations for the modern enterprise. Our AIOps platform empowers organizations to achieve Autonomic IT — where systems are self-healing, self-optimizing, and seamlessly aligned with business outcomes. We help enterprises and service providers gain unified visibility across hybrid and multi-cloud environments, automate workflows, and unlock performance at scale.
We’re accelerating digital transformation through the power of automation, AI, and analytics — giving IT and business leaders the tools to deliver superior customer experiences, drive efficiency, and innovate with confidence.

 

Role Overview-

We are seeking a passionate and capable Platform Engineer with experience of 5- 8 years to be part of our Skylar AI Platform team - our next-generation AI-powered observability platform. This role is key to ensuring we maintain regular software updates on a monthly cadence to our Skylar AI platform. You will ensure that the lab environment is always available to the engineering team. You will be the go-to person in Product Engineering for End-to-End testing on Skylar AI, using AI to help solve problems, resolve tickets, and provide clear status updates. You'll enable Product Management, Data Science, Quality, and Engineering teams to use the platform to verify and test as much as possible.

 

Responsibilities

 
  • Lab Creation: Deploy & maintain a lab environment which will be used for development, testing, and staging. This will build on existing lab work that has been done and will support multiple environment types.

  • Deployment pipelines: Automated tests trigger on every commit → validate builds → confirm staging matches production

  • Cross-system workflows: Test data flowing from ingestion → Skylar AI processing → telemetry capture → reporting dashboards

  • User journeys: Simulate real platform usage end-to-end; catch breaks before users do

  • Regression prevention: Maintain test suites that catch when new features break existing functionality

  • Performance gates: Automated testing validates response times, throughput, and resource consumption

  • Integration testing: Verify third-party APIs, databases, and services work correctly together

  • Rollback validation: Tests confirm systems safely recover after failed deployments

  • Keeping Versions Current: Setting up and keeping Skylar One/Advisor/Analytics (Dev + Stable), and other data sources current, operating, and in sync.

  • Data Generation: Setup and maintain telemetry generation whether from existing sources such as SkylarOne or workload simulations

  • Documentation: Ensure that documentation of the environment, processes, and uses are kept up to date

 

Skills

 

Core Programming & API

  • API use and integration, REST/GraphQL principles

  • Node.js and/or Python with a focus on automation development

  • Full-stack debugging and troubleshooting

  • ·JavaScript/TypeScript frontend development to be able to work with our front end teams

 

Testing & QA

  • Test data generation and management

  • CI/CD pipeline automation (GitHub, Gitops, etc)

  • Test automation frameworks (Playwright)

  • Load/performance testing tools (k6, jmeter, etc)

 

Infrastructure & DevOps

  • Docker and Kubernetes fundamentals

  • Monitoring and observability tools (SkylarOne, Prometheus, Grafana, etc)

  • Database optimization and query performance to help resolve issues found in testing

 

Telemetry & ServiceNow

  • Event logging and metrics collection

  • Trace aggregation and analytics platforms (OpenTelemetry)

  • Management of ServiceNow

  • ServiceNow incident/change management workflows

  • ITSM best practices and ticketing

 
  • AI Platform Knowledge

  • LLM API consumption and integration

  • Prompt engineering basics

  • AI system debugging and validation

 

Collaboration

  • Cross-functional partnership with engineering, product, and data science

  • Proactive issue identification and escalation

  • Technical documentation and knowledge sharing
    Don’t meet every single requirement? Studies have shown that women and people of color are less likely to apply to jobs unless they meet every single qualification. At ScienceLogic, we are dedicated to building a diverse, inclusive and authentic workplace, so if you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles.

 

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, or any other applicable legally protected characteristics in the location in which you are applying.

 
 
About ScienceLogic

ScienceLogic is a leader in IT Operations Management, providing modern IT operations with actionable insights to resolve and predict problems faster in a digital, ephemeral world. Its solution sees everything across cloud and distributed architectures, contextualizes data through relationship mapping, and acts on this insight through integration and automation.

 

www.sciencelogic.com

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