Platform Engineer I

The role

This person will improve the stability, reliability, and efficiency of a global SaaS platform through automation solutions and platform tools. They will design and maintain automation tools, build internal workflows, and develop observability and monitoring solutions.

What you will do

• Design, develop, and maintain automation tools and platform capabilities using Go, Python, or similar languages.
• Build and enhance internal tools, integrations, and workflows.
• Develop and support automation frameworks for incident response, infrastructure testing, monitoring optimization, and compliance validation.
• Help develop observability and monitoring solutions including alerts, noise reduction, SLO management, and cost optimization.
• Partner with SaaS Engineering to deploy application and infrastructure updates using automation tools.
• Available for on-call duties for incident response and blameless postmortems.
• Contribute to build playbook documentation and procedures.

Required qualifications

• Bachelor’s degree in Computer Science, Engineering, or a related field (equivalent work experience will be considered in lieu of a degree).
• 3-5 years of experience in software development, platform engineering, Site Reliability Engineering (SRE), or DevOps.
• Hands-on experience supporting production environments.
• Technical expertise in Kubernetes, cloud platforms (AWS, Azure, or GCP), Go/Python development, Linux, Infrastructure as Code (Terraform, CloudFormation, Ansible), CI/CD, container technologies, APIs,
• Familiarity with AI-assisted tools such as Microsoft Copilot, GitHub Copilot, Claude, Cursor, or similar tools.
• Ability to leverage AI tools to improve infrastructure automation, scripting, documentation, test generation, and engineering productivity.
• Familiarity with LLM APIs and agentic AI workflows.
• Awareness of responsible AI principles, including security, bias, explainability, and appropriate use of AI-generated outputs.

Nice to have

• Experience contributing to automation projects, internal tools, or monitoring implementations (i.e. Datadog, Prometheus, Grafana, Backstage).
• Experience with Kubernetes operators, controllers, or orchestration concepts.
• FedRAMP, SOC2, or compliance framework exposure.

About the company

Precisely is a global leader in data quality, data enrichment, and location intelligence. It is an AI-first organization that helps brands make decisions with reliable data.