Platform Engineer

Our client, a Health Insurance company, is looking for a Platform Engineer for their Plano, TX/Hybrid location.

Responsibilities:

• The Senior Associate Platform Engineer contributes to the development, configuration, and support of platform services, automation solutions, and cloud-based infrastructure.
• Assists in building and maintaining automation frameworks, reusable tools, and platform capabilities that improve engineering efficiency, reliability, and software delivery.
• Supports the implementation of CI/CD workflows, infrastructure automation, and platform observability while adopting modern engineering practices and AI-enabled tools under guidance.
• Collaborates with engineering, product, and platform teams to deliver scalable solutions, streamline development workflows, and support continuous improvement across the AI-driven development lifecycle.
• This role specializes in SDLC automation and intelligent engineering, focusing on building reusable frameworks, components, and self-service capabilities that accelerate software delivery.
• Engineers leverage modern programming languages, automation platforms, data-driven insights, CI/CD integration, and AI-powered tools to improve platform reliability, reduce maintenance effort, enhance developer productivity, and enable autonomous workflows across the AIDLC.
• Essential Job Functions:
• Platform Engineering & Platform Capabilities: Design and maintain scalable engineering platforms, products, and shared services.
• Build reusable APIs, SDKs, frameworks, and self-service capabilities.
• Improve developer productivity, operational efficiency, and scalability.
• Establish secure delivery guardrails and standards.
• Reduce manual effort through automation and reusable solutions.
• Intelligent Automation, AI Enabled Engineering:
• Design and implement intelligent automation and AI-driven engineering solutions. Build scalable automation capabilities, platform services, AI agents, and engineering tools.
• Drive adoption of automation-first and AI-assisted engineering practices.
• Automate development, testing, deployment, operations, governance, and security processes.
• Establish reusable automation patterns and workflows.
• Partner with teams to embed AI, automation, and guardrails across software delivery.
• AI Engineering & Agent Platforms:
• Build AI-powered engineering capabilities, workflows, and developer experiences.
• Develop AI agents and autonomous workflows that improve productivity.
• Integrate LLMs, prompt engineering, context management, and AI orchestration frameworks.
• Implement MCP, RAG, tool integrations, and agent-based solutions.
• Evaluate and adopt emerging AI technologies and frameworks.
• Developer Experience & Self-Service Engineering:
• Design and enhance internal developer platforms that simplify engineering workflows.
• Build self-service capabilities that reduce dependencies and accelerate delivery.
• Improve onboarding, development, testing, deployment, and support experiences.
• Develop reusable templates, automation assets, and engineering accelerators.
• Promote platform adoption through documentation and enablement.
• Advocate developer-centric design and continuous improvement.
• Platform Operations, Reliability & Delivery Enablement:
• Integrate platform capabilities into engineering workflows, CI/CD pipelines, and operations.
• Build solutions that improve reliability, resilience, scalability, and operational readiness.
• Implement automated controls, governance, deployment guardrails, and policy enforcement.
• Enable intelligent operations through automation, AI-assisted insights, and root-cause analysis.
• Leverage IaC, cloud-native architecture, and automation.
• Support adoption of modern platform engineering and DevOps practices.
• Security, Governance & Engineering Controls:
• Build security controls and governance capabilities into engineering platforms.
• Implement secure-by-design principles and automation across the software delivery lifecycle.
• Develop automated compliance validation, policy enforcement, and risk management capabilities.
• Establish guardrails that balance engineering agility with organizational requirements.
• Partner with security and architecture teams to align with enterprise standards.
• Continuously improve platform security through automation and proactive practices.

Requirements:

• 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
• 2-5 years of related work experience in hands-on programming experience with one or more modern programming languages.
• Experience designing and building scalable automation solutions, engineering platforms, developer tools, reusable components, shared services, or self-service capabilities and relevant experience working across areas of Platform engineering.
• Relevant industry certifications in cloud platforms, DevOps, platform engineering, software development, automation, AI/ML, data engineering, or related technologies are preferred.
• Skills:
• Platform Engineering & Architecture
• Developer Experience (DevEx) & Self-Service Platforms
• Reusable Components, APIs, SDKs & Shared Services
• Automation & AIDLC Enablement
• AI-Assisted Engineering & AI Agents
• Cloud Engineering (AWS) & Cloud-Native Platforms
• DevOps, CI/CD
• Monitoring, Observability & Reliability Engineering
• RAG Systems, MCP Integrations & AI Tool Integration (GitHub Copilot, AWS Kiro, Bedrock)
• Observability, Debugging & Failure Analysis
• LLM Workflows, Prompt Engineering & Context Engineering
• AI Agents, Agent Orchestration & Workflow Automation

Why Should You Apply?

• Health Benefits
• Referral Program
• Excellent growth and advancement opportunities