Principal AI & Analytics Platform Engineer

Overview

Client is seeking a Principal AI & Analytics Platform Engineer to lead the architecture, engineering, and evolution of an enterprise AI and analytics platform. This is a strategic, hands-on individual contributor role focused on building scalable cloud-native data platforms, AI-enabled applications, and modern analytics solutions.

The engineer will partner with executive leadership, product teams, data scientists, business stakeholders, and engineering organizations to define and implement enterprise AI and analytics strategies. The platform will process billions of rows of data while supporting advanced analytics, generative AI, machine learning, intelligent automation, and customer-facing applications.

Core Responsibilities

• Architect and build enterprise-scale AI and analytics platforms.
• Design secure, multi-tenant architectures for internal users and external customer-facing applications.
• Develop cloud-native solutions supporting analytics, machine learning, generative AI, automation, and operational intelligence.
• Build foundational data architectures using Snowflake, Snowpark, Snowflake Cortex, LLMs, vector search, and modern AI frameworks.
• Establish architecture standards for scalability, resiliency, security, governance, performance, and cost optimization.
• Design and optimize high-volume ETL and ELT pipelines.
• Model and optimize billions of rows of data using dimensional, normalized, and Data Vault methodologies.
• Optimize Snowflake through clustering, workload management, query optimization, caching, and cost-management strategies.
• Develop solutions using SQL, Python, Snowpark, APIs, automation frameworks, and cloud-native services.
• Integrate LLM APIs, machine learning models, Snowflake Cortex, and other AI services into production applications.
• Develop predictive analytics, natural-language interfaces, AI copilots, and workflow automation capabilities.
• Build modern React applications, interactive visualizations, and dashboards for large-scale analytical workloads.
• Develop secure and scalable backend APIs using Python, Node.js, TypeScript, or comparable technologies.
• Optimize frontend performance using virtualization, caching, state management, and Web Workers.
• Implement row-level security, data isolation, access controls, and enterprise governance frameworks.
• Develop technical roadmaps and present architecture strategies, risks, recommendations, and business impacts to senior leadership.
• Lead proofs of concept, technology evaluations, and AI innovation initiatives.
• Mentor engineering teams and establish architectural patterns, engineering standards, and development best practices.

Essential Qualifications, Skills, and Technologies

• 8+ years of experience in software engineering, data engineering, analytics engineering, or cloud platform development.
• 5+ years of enterprise experience building solutions with Snowflake.
• Expert-level SQL and Python development skills.
• Deep expertise with Snowpark, Snowflake Cortex, Streams, Tasks, and enterprise Snowflake optimization.
• Strong experience with Node.js, TypeScript, or comparable backend technologies.
• Expertise developing React applications for large-scale analytical datasets.
• Experience optimizing frontend performance through virtualization, advanced caching, state management, and Web Workers.
• Experience designing dimensional, normalized, and Data Vault data architectures.
• Extensive experience building enterprise ETL and ELT pipelines.
• Experience with AWS, Microsoft Azure, and/or Google Cloud Platform.
• Experience designing APIs, automation frameworks, and cloud-native services.
• Hands-on experience integrating LLMs, AI services, machine learning platforms, and enterprise AI frameworks into production applications.
• Experience designing secure, multi-tenant enterprise platforms.
• Experience implementing row-level security, customer data isolation, and secure data-access models.
• Strong understanding of enterprise security, governance, privacy, compliance, and responsible AI practices.
• Experience using AI-assisted development tools while maintaining engineering quality through testing, review, and optimization.
• Demonstrated ability to present technical strategy and architecture to VP and C-suite audiences.
• Ability to lead through technical expertise and influence in a principal individual contributor capacity.

Preferred Skills or Experience

• Experience building enterprise AI platforms and AI engineering frameworks.
• Experience with Retrieval-Augmented Generation, vector databases, embeddings, semantic search, and AI orchestration frameworks.
• Familiarity with MLOps, model lifecycle management, and AI governance.
• Experience with Kubernetes, containerization, Infrastructure as Code, and CI/CD automation.
• Experience supporting customer-facing SaaS analytics platforms.
• Knowledge of observability, platform reliability engineering, and distributed systems architecture.

Work Details

• Remote, US-based role.
• Open to candidates across all US time zones.