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TM

Platform Engineer

Tailored Management
🇺🇸 United States
On-site
Senior
3 weeks ago
  • Devops
  • AI
  • AI/ML
  • Cloud Practitioner
  • Azure
  • GCP
  • AWS Cloud
  • CI/CD
  • IaC
  • RAG
  • MCP
  • AWS
  • Amazon Bedrock
3 weeks ago
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Job Title: Platform Engineer
Location: Plano, TX 75024 (Hybrid) – 1–2 days per week onsite (Candidate must be locatedwithin a 60-mile radius of a Bread Financial location. -No California candidates.
Duration: 06-month contract (Temp-to-Hire.)
Start Date: Targeting Oct 2026
Pay Rate: $53.57/hr. on W2
Benefits: Medical, Dental, Vision.
Hours:8:00 AM – 5:00 PM as per time zone
 
Job Description:
  • We are seeking a Senior Associate Platform Engineer to help design, develop, and support scalable platform services, automation solutions, and cloud-based infrastructure. This role focuses on Platform Engineering, SDLC automation, Developer Experience, Cloud Engineering, DevOps, and AI-enabled engineering.
  • The engineer will build reusable frameworks, APIs, SDKs, shared services, self-service capabilities, automation solutions, and AI-powered engineering tools that improve developer productivity, platform reliability, and software delivery.
Minimum Qualifications:
  • Bachelor’s degree in Information Technology, Computer Science, Computer Information Systems, Software Engineering, Mathematics, Statistics, or a related field, or equivalent relevant work experience.
  • 2–5 years of related professional experience.
  • 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.
  • Relevant experience working across Platform Engineering.
Preferred Qualifications:
  • Industry certifications in cloud platforms, DevOps, Platform Engineering, software development, automation, AI/ML, data engineering, or related technologies.
  • Experience with AI-assisted engineering, AI agents, or intelligent automation.
Required Certification:
  • Candidates must possess at least one of the following certifications:
  • AWS Certified Cloud Practitioner
  • Microsoft Azure Fundamentals
  • Google Cloud Digital Leader
Required Skills
  • Platform Engineering & Architecture
  • Developer Experience (DevEx) & Self-Service Platforms
  • APIs, SDKs, Reusable Components & Shared Services
  • Automation & AIDLC Enablement
  • AI-Assisted Engineering & AI Agents
  • AWS Cloud & Cloud-Native Platforms
  • DevOps & CI/CD
  • Monitoring, Observability & Reliability Engineering
  • Infrastructure as Code (IaC)
  • RAG Systems & MCP Integrations
  • AI Tool Integration, including GitHub Copilot, AWS Kiro, and Amazon Bedrock
  • LLM Workflows, Prompt Engineering & Context Engineering
  • Agent Orchestration & Workflow Automation
  • Debugging, Failure Analysis & Root-Cause Analysis
Key Responsibilities:
  • Design and maintain scalable engineering platforms, products, and shared services.
  • Build reusable APIs, SDKs, frameworks, templates, and self-service capabilities.
  • Develop intelligent automation and AI-driven engineering solutions.
  • Build AI agents, autonomous workflows, and AI-powered developer experiences.
  • Integrate LLMs, RAG, MCP, prompt engineering, context management, and AI orchestration frameworks.
  • Integrate platform capabilities into CI/CD pipelines and engineering workflows.
  • Improve developer productivity, software delivery, reliability, scalability, and operational efficiency.
  • Automate development, testing, deployment, operations, governance, security, and compliance processes.
  • Implement deployment guardrails, automated controls, policy enforcement, and governance capabilities.
  • Leverage cloud-native architectures, AWS, Infrastructure as Code, and modern DevOps practices.
  • Build monitoring and observability solutions to improve platform reliability and operational readiness.
  • Develop reusable automation patterns and engineering accelerators.
  • Partner with engineering, product, security, architecture, and platform teams to deliver scalable solutions.
  • Evaluate and adopt emerging AI, automation, and platform engineering technologies.
  • Continuously improve developer experience, platform adoption, security, and engineering efficiency.
Interview Process:
  • Round 1: Technical Interview
  • Round 2: Design / Architecture / Solution Interview
 
#TMN

Platform Engineer · Tailored Management

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