CONFIDENTIAL: Principal Platform Engineer

Job Description

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.

Responsibilities

Enterprise AI Strategy & ArchitectureDefine 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 EngineeringArchitect 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 & InnovationResearch 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 & SecurityImplement 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 AdoptionEnable 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 & CollaborationProvide 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.

Skills and Requirements

10+ years of experience in platform engineering, cloud infrastructure, software engineering, or enterprise architecture.Enterprise AI Infrastructure & LLMOps / MLOps Architecture - Cloud AI Ecosystems: Deep architectural expertise in enterprise cloud AI suites (e.g., Azure AI Studio, AWS Bedrock, Google Cloud Vertex AI) to build and provision scalable developer environments.Proven experience building and operating enterprise AI/ML platforms in production, with ownership of platform architecture, scalability, governance, and adoption.Deep expertise in Vertex AI and MLOps, including training pipelines, model registry, evaluation and approval workflows, and model serving.Hands-on experience with Generative AI platforms, including model access and lifecycle management, prompt management, RAG, grounding, guardrails, evaluation frameworks, AI agents, and MCP integration.Strong platform engineering and automation background, including Terraform, infrastructure-as-code, policy-as-code, CI/CD pipelines, and reusable self-service platform templates.Experience implementing observability and FinOps practices for AI platforms, including tracing, drift detection, latency monitoring, token usage tracking, and cost optimization.Advanced Python software engineering skills with a demonstrated ability to make and own critical architecture decisions.

We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal employment opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment without regard to race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or the recruiting process, please send a request to View email address on click.appcast.io.