There are 3 roles for Devops Engineers, each at a different level.
Platform engineer - (2-5 Years)
SR platform engineer - (5-8 Years of experience)
Staff platform engineer - (10 Years of experience)
Location is Plano TX, - local candidates only.
PRIORITY
ONE OF THESE CERTIFICATIONS IS REQUIRED FOR ANY CANDIDATE SUBMITTED
- AWS cloud practitioner,
- Microsoft Azure Fundamentals
- Google Cloud- Cloud Digital Leader
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Minimum Qualifications
- Bachelor's degree in information technology, Computer Science, Computer Information Systems, Software Engineering, Mathematics, Statistics or related field of study or equivalent, relevant work experience
- 5-8 years of experience in platform engineering, software engineering, cloud engineering, DevOps, automation engineering, or related disciplines. Strong hands-on experience with modern programming languages, cloud-native technologies, automation frameworks, and engineering platforms.
- Proven experience designing and delivering scalable platform solutions, shared services, automation frameworks, reusable components, developer tools, and self-service capabilities.
- Demonstrated experience leading technical initiatives and driving adoption of engineering best practices across teams.
Preferred Qualifications
- Relevant industry certifications in cloud platforms, DevOps, platform engineering, software development, automation, AI/ML, data engineering, or related technologies are preferred.
Skills
- Platform Engineering Strategy & Architecture
- Engineering Platforms, Platform Products & Shared Services
- Developer Experience (DevEx) & Self-Service Platforms
- Reusable Components, APIs, SDKs, Frameworks & Accelerators
- Intelligent Automation & AIDLC Enablement
- AI-Assisted Engineering & Agent-Based Development
- Platform Modernization & Cloud-Native Architectures
- Cloud Engineering & Infrastructure as Code (IaC)
- DevOps, CI/CD & Engineering Productivity
- Site Reliability Engineering (SRE) & Operational Excellence
- Monitoring, Observability & Platform Reliability
- Security, Governance & Engineering Controls
The Senior Platform Engineer leads the design, development, and evolution of platform services, automation solutions, and cloud-native engineering capabilities that improve software delivery, reliability, scalability, security, and developer productivity. This role drives the creation of reusable platform products, shared services, self-service capabilities, and intelligent automation solutions while establishing engineering standards and best practices. Collaborating across engineering, product, architecture, security, and operations teams, the Senior Platform Engineer enables scalable platform adoption and advances organizational platform maturity across the AI-Driven Development Lifecycle (AIDLC).
This role specializes in SDLC automation and intelligent engineering, driving the architecture, standardization, and adoption of reusable frameworks, platform products, components, and self-service capabilities. Engineers leverage modern engineering practices, cloud-native technologies, AI-powered solutions, and agent-based automation to accelerate software delivery, improve platform reliability, enhance developer productivity, and enable intelligent autonomous workflows across the AIDLC.
Essential Job Functions
- Platform Engineering & Platform Capabilities: Lead the design and evolution of scalable engineering platforms, products, and shared services. Architect reusable APIs, SDKs, frameworks, and self-service capabilities. Establish platform standards, patterns, and engineering practices. Drive platform modernization and cloud-native adoption. Implement governance guardrails for secure, compliant software delivery. Partner with teams to deliver enterprise solutions and improve developer experience.
- Intelligent Automation, AI Enabled Engineering: Lead development of intelligent automation solutions across the AI-Driven Development Lifecycle. Architect scalable automation frameworks, AI services, and platform capabilities. Drive adoption of automation-first and AI-assisted engineering practices. Design automation for development, testing, deployment, operations, governance, and security. Lead implementation of AI agents and intelligent workflows. Collaborate with teams to embed automation across engineering ecosystems.
- AI Engineering & Agent Platforms: Lead development of AI-powered engineering capabilities, autonomous workflows, and developer experiences. Architect and implement AI agents, orchestration frameworks, and agent-based solutions. Integrate LLMs, prompt engineering, context engineering, MCP, and RAG capabilities. Define standards and best practices for AI-enabled engineering. Evaluate emerging AI technologies and establish scalable adoption patterns.
- Developer Experience & Self-Service Engineering: Lead initiatives that improve developer experience through self-service platforms and enablement capabilities. Define standards and best practices for developer workflows. Build reusable templates, accelerators, and automation assets that increase efficiency. Drive platform adoption through technical leadership and enablement. Enhance engineering workflows using feedback and operational insights. Advocate developer-centric platform design and engineering excellence.
- Platform Operations, Reliability & Delivery Enablement: Lead integration of platform capabilities into engineering workflows, CI/CD pipelines, and operations. Design highly available, resilient, scalable, and observable platform solutions. Define deployment standards, governance controls, and reliability practices. Implement observability, operational intelligence, anomaly detection, and automated remediation. Drive adoption of IaC, cloud-native architectures, and automation. Use operational metrics and insights to improve platform performance and reliability.
- Security, Governance & Engineering Controls: Design and implement platform-wide security controls and governance capabilities. Establish secure-by-design practices and automated compliance controls. Lead policy enforcement, risk management, and compliance automation solutions. Define technology guardrails that balance agility and governance requirements. Partner with security, risk, and architecture teams to align with organizational standards. Continuously improve security through automation and proactive engineering initiatives.
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