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