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Senior Platform Engineer
Required Certification
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
Position Summary
The Senior Platform Engineer is responsible for designing, developing, and evolving enterprise platform services, automation solutions, and cloud-native engineering capabilities that improve software delivery, reliability, scalability, security, and developer productivity.
This role focuses on platform engineering, SDLC automation, cloud technologies, and AI-enabled engineering. The Senior Platform Engineer develops reusable platform products, shared services, APIs, frameworks, and self-service capabilities while establishing engineering standards and best practices.
Working closely with engineering, architecture, product, security, and operations teams, this role enables adoption of modern engineering practices and advances platform capabilities across the AI-Driven Development Lifecycle (AIDLC).
Key Responsibilities
Platform Engineering & Cloud Architecture
- Design and develop scalable engineering platforms, shared services, and reusable platform capabilities.
- Build APIs, SDKs, frameworks, templates, and accelerators that enable engineering teams to deliver software efficiently.
- Establish and implement platform standards, architecture patterns, and engineering best practices.
- Drive cloud-native modernization and adoption of modern engineering technologies.
- Implement appropriate governance and security guardrails for scalable, compliant software delivery.
Intelligent Automation & AI-Enabled Engineering
- Design and implement automation solutions across the software development lifecycle.
- Develop automation frameworks and platform capabilities supporting development, testing, deployment, operations, governance, and security.
- Promote automation-first and AI-assisted engineering practices.
- Develop intelligent workflows and AI-powered solutions that improve engineering productivity and efficiency.
- Identify opportunities to automate repetitive engineering processes and improve delivery outcomes.
AI Engineering & Agent-Based Development
- Design and implement AI-enabled engineering capabilities and intelligent developer workflows.
- Develop and integrate AI agents, orchestration frameworks, and agent-based solutions.
- Work with LLMs, prompt engineering, context engineering, MCP, and RAG technologies.
- Evaluate emerging AI technologies and identify practical enterprise applications.
- Establish scalable patterns and best practices for incorporating AI into engineering platforms.
Developer Experience & Self-Service
- Develop self-service platforms and tools that improve developer productivity and autonomy.
- Create reusable templates, accelerators, automation assets, and development workflows.
- Improve developer onboarding, development, testing, deployment, and support processes.
- Drive adoption of platform capabilities through technical leadership, documentation, and enablement.
- Use developer feedback and platform metrics to continuously improve the engineering experience.
DevOps, Reliability & Platform Operations
- Integrate platform capabilities with CI/CD pipelines and engineering workflows.
- Design highly available, resilient, scalable, and observable platform solutions.
- Implement Infrastructure as Code (IaC), deployment automation, monitoring, and operational intelligence.
- Apply SRE principles to improve platform reliability and performance.
- Implement anomaly detection, automated remediation, and intelligent operational workflows.
- Use operational metrics and insights to identify opportunities for continuous improvement.
Security & Governance
- Implement platform-level security, governance, compliance, and risk controls.
- Apply secure-by-design principles throughout platform development and engineering workflows.
- Automate policy enforcement and compliance controls where appropriate.
- Establish technology guardrails that balance engineering agility with security and governance requirements.
- Partner with security, risk, and architecture teams to ensure alignment with enterprise standards.
Minimum Qualifications
- Bachelor’s degree in Information Technology, Computer Science, Computer Information Systems, Software Engineering, Mathematics, Statistics, or a related field; equivalent relevant experience may be considered.
- 5–8 years of experience in platform engineering, software engineering, cloud engineering, DevOps, automation engineering, or a related technical discipline.
- Hands-on experience with modern programming languages, cloud-native technologies, automation frameworks, and engineering platforms.
- Experience designing and delivering scalable platform solutions, shared services, automation frameworks, reusable components, developer tools, or self-service capabilities.
- Experience leading technical initiatives and driving adoption of engineering standards and best practices across multiple teams.
- Strong understanding of cloud engineering, DevOps, CI/CD, Infrastructure as Code, automation, and modern software delivery practices.
- At least one required cloud certification: AWS Cloud Practitioner, Microsoft Azure Fundamentals, or Google Cloud Digital Leader.
Preferred Qualifications
- Experience with AI-assisted software development, intelligent automation, AI agents, or agent-based engineering.
- Experience with LLMs, RAG, MCP, prompt engineering, context engineering, or AI orchestration frameworks.
- Experience building enterprise developer platforms or self-service engineering capabilities.
- Experience with SRE, observability, platform reliability, and operational automation.
- Additional certifications in cloud, DevOps, platform engineering, software development, AI/ML, or related technologies.