Platform Engineer

ECLARO; Quezon City; On-site; PHP 900,000 - 1,300,000; Full time

Job summary

ECLARO is seeking a Platform Engineer in the Philippines to build and maintain a shared cloud platform and engineering foundations for data and AI workloads. The role emphasizes AWS platform engineering, reusable services, DevSecOps, observability, and standards-based architecture, collaborating with multiple teams to enforce governance and security.

Responsibilities include automating platform delivery, improving developer productivity, and standardizing integration patterns while mentoring

Qualifications

• 5 years of experience in platform engineering, cloud infrastructure, DevOps, or SRE.
• Strong experience with AWS and infrastructure support for modern data workloads.
• Experience enabling engineering teams through CI/CD, GitLab, observability, reusable services, and platform standards.

Responsibilities

• Build and maintain shared platform services in AWS for applications, data products, and AI workloads.
• Standardize delivery patterns for APIs, compute, storage, monitoring, and secure service integration.
• Improve developer productivity through CI/CD, environment templates, internal tooling, and platform automation.
• Implement platform observability, reliability practices, cost-aware resource management, and secure secrets/access patterns.
• Support reusable engineering standards aligned with cloud-native platforms and composable architectures.
• Partner with architecture, security, and engineering leaders to apply controls, interoperability standards, and governance guardrails.
• Document platform standards and help delivery teams adopt them consistently.

Skills

Platform engineering

AWS

CI/CD

Python

GitLab

Observability

Security basics

Tools

Databricks

Kubernetes

Git

Job description

Role Title: Platform Engineer

ECLARO:

A quick Summary

ECLARO is an award-winning professional services firm headquartered in New York City and operating in the U.S., Canada, UK, Ireland, Australia and the Philippines. We are dedicated to a singular purpose: providing the Right People to meet every client's needs and solve business challenges through strategic staffing, permanent placement, custom outsourcing & offshoring. Utilizing our proprietary TRINIT-E® Service Maturity Model, we help clients implement programs to promote innovation, automation and process improvement.

About the Role:

The Platform Engineer builds the shared cloud platform and engineering foundations that enable AIDA teams to deliver secure, scalable, cloud-native data and AI products. This role focuses on AWS platform engineering, reusable services, DevSecOps, observability, and standards-based architecture.

Key Responsibilities:

• Build and maintain shared platform services in AWS for applications, data products, and AI workloads.
• Standardize delivery patterns for APIs, compute, storage, monitoring, and secure service integration.
• Improve developer productivity through CI/CD, environment templates, internal tooling, and platform automation.
• Implement platform observability, reliability practices, cost-aware resource management, and secure secrets/access patterns.
• Support reusable engineering standards aligned with cloud-native platforms and composable architectures.
• Partner with architecture, security, and engineering leaders to apply controls, interoperability standards, and governance guardrails.
• Document platform standards and help delivery teams adopt them consistently.

Qualifications:

• 5 years of experience in platform engineering, cloud infrastructure, DevOps, or SRE.
• Strong experience with AWS and infrastructure support for modern application and data workloads.
• Experience enabling engineering teams through CI/CD, GitLab, observability, reusable services, and platform standards.
• Strong coding or scripting ability in Python; Java or NodeJS is a plus.
• Experience supporting containers, API infrastructure, deployment pipelines, and operational tooling.

Preferred Qualifications:

• Experience supporting Databricks, data platforms, and AI/ML workloads.
• Exposure to regulated enterprise environments, identity/access controls, and audit logging.