Platform Engineer

Insight Global is in search for a Principal Platform Engineer to architect and oversee the infrastructure for a Global Fashion Retailer. This is a strategic leadership role responsible for defining AI platform architecture, governance, scalability, and developer enablement across the organization. Reporting into a senior technology leadership team, this individual will bridge emerging AI capabilities with practical business applications while establishing the technical foundations required to securely develop, deploy, and manage AI solutions at scale. This role is ideal for someone who thrives at the intersection of platform engineering, cloud architecture, AI innovation, and enterprise transformation.

Location: Seattle, WA - 3+ days a week onsite

Duration: Full Time

Salary: $100,000 - $300,000+ (Based on applicable experience)

Maximise your chances of a successful application to this job by ensuring your CV and skills are a good match.

Responsibilities:

Enterprise AI Strategy & Architecture

• Define the long-term vision, principles, and technical standards for enterprise AI platforms.
• Develop and maintain an AI platform roadmap aligned with business and technology priorities.
• Design scalable AI architecture that supports current and future AI initiatives.
• Evaluate and manage strategic relationships with AI vendors, platform providers, and technology partners.

AI Platform Engineering

• Architect and build enterprise-grade AI platforms and developer environments.
• Enable secure AI development through modern tooling, infrastructure, and automation.
• Support the deployment and scaling of AI-powered applications and services.
• Establish reusable frameworks, patterns, and best practices for AI engineering teams.

AI Enablement & Innovation

• Research emerging AI technologies and assess their practical application within the enterprise.
• Lead proof-of-concept initiatives and feasibility assessments for new AI opportunities.
• Partner with cross-functional stakeholders to identify and prioritize high-impact use cases.
• Drive innovation while balancing security, governance, and operational requirements.

AI Governance & Security

• Implement secure-by-design principles across AI platforms and services.
• Establish monitoring, compliance, and governance controls for responsible AI usage.
• Partner with cybersecurity, risk, and compliance teams to ensure adherence to regulatory and ethical standards.
• Develop frameworks for platform observability, model monitoring, and risk mitigation.

Enterprise AI Adoption

• Enable AI-powered productivity tools, intelligent assistants, and enterprise search capabilities.
• Champion AI literacy and best practices across both technical and business teams.
• Contribute to organizational AI standards, documentation, and enablement programs.
• Foster a culture of experimentation, learning, and responsible AI adoption.

Leadership & Collaboration

• Provide technical leadership and mentorship to engineers and platform teams.
• Partner with executive, business, and technology leaders to influence AI strategy and investment decisions.
• Drive alignment across architecture, engineering, security, data, and product teams.
• Promote engineering excellence, collaboration, and continuous improvement.

Qualifications:

• 10+ years of experience in platform engineering, cloud infrastructure, software engineering, or enterprise architecture.
• Experience designing and operating enterprise-scale AI, machine learning, or data platforms.
• Strong expertise with cloud platforms such as Azure, AWS, or Google Cloud.
• Experience building developer platforms, automation frameworks, and scalable infrastructure.
• Knowledge of AI/ML platforms, LLMs, RAG architectures, vector databases, and AI observability.
• Strong understanding of enterprise security, governance, compliance, and risk management.
• Proven ability to lead complex technical initiatives and influence executive stakeholders.

Preferred Experience:

• Enterprise AI platform implementation.
• LLMOps, MLOps, and AI infrastructure engineering.
• Generative AI, Retrieval-Augmented Generation (RAG), and AI orchestration frameworks.
• AI governance, model monitoring, and responsible AI practices.
• Large-scale digital transformation initiatives. xhyhwjd

We offer a comprehensive benefits package designed to support your health, financial well-being, and work-life balance.