Platform Engineer

Senior Associate Platform Engineer

Location: Plano, TX – Hybrid, 1–2 days per week in office

Candidates must hold at least one of the following certifications. A copy of the certification must be provided with the submission:

• AWS Certified Cloud Practitioner
• Microsoft Azure Fundamentals
• Google Cloud Digital Leader

The Senior Associate Platform Engineer supports the development, configuration, and maintenance of enterprise platform services, automation solutions, and cloud-based infrastructure. This role builds reusable tools, frameworks, platform capabilities, and self‑service solutions that improve engineering productivity, software delivery, reliability, and operational efficiency.

The role has a strong focus on SDLC automation, cloud engineering, Dev Ops, and AI-enabled development
. The Senior Associate Platform Engineer works with engineering and platform teams to implement CI/CD pipelines, infrastructure automation, observability, developer tools, and AI-powered solutions across the AI-Driven Development Lifecycle (AIDLC).

The ideal candidate is a hands‑on engineer who enjoys solving technical problems, automating manual processes, building reusable solutions, and applying emerging technologies to improve software engineering workflows.

• Build and maintain scalable platform services, shared services, and engineering capabilities.
• Develop reusable APIs, SDKs, frameworks, templates, and developer tools.
• Build self‑service capabilities that simplify development and reduce engineering dependencies.
• Improve developer onboarding, development, testing, deployment, and support workflows.
• Establish and follow platform engineering standards, patterns, and secure delivery practices.

• Design and implement automation solutions across the software development lifecycle.
• Automate development, testing, deployment, operations, governance, and security processes.
• Build reusable automation frameworks, workflows, and engineering tools.
• Leverage AI‑assisted development tools to improve engineering productivity and reduce manual effort.
• Support the implementation of AI agents and intelligent workflows across engineering processes.

• Build AI‑powered engineering capabilities and developer experiences.
• Develop and integrate AI agents, workflow automation, and agent orchestration solutions.
• Work with LLMs, prompt engineering, context engineering, RAG, and MCP integrations.
• Integrate AI tools and platforms such as Git Hub Copilot, AWS Kiro, and Amazon Bedrock
  .
• Evaluate emerging AI technologies and identify opportunities to improve engineering efficiency.

• Develop and support cloud‑native solutions, primarily within AWS environments.
• Implement and maintain CI/CD pipelines and automated deployment processes.
• Support Infrastructure as Code (IaC), cloud automation, and modern Dev Ops practices.
• Build reliable, scalable, and secure platform capabilities.
• Implement automated controls, deployment guardrails, and policy enforcement.

• Implement monitoring, logging, observability, and operational intelligence capabilities.
• Troubleshoot platform and application issues and perform root‑cause analysis.
• Support reliability, resilience, scalability, and performance improvements.
• Leverage automation and AI‑assisted tools to identify and resolve operational issues.
• Use operational metrics and insights to continuously improve platform performance.

• Incorporate security and governance controls into platform and engineering solutions.
• Support secure‑by‑design practices throughout the software development lifecycle.
• Implement automated…