OVERVIEW

We are looking for a Lead Data & AI Platform Engineer to architect, build, and evolve the foundational platforms that power data science, advanced analytics, and AI across the company. This role is for a deeply experienced builder who has designed production-grade AI systems end to end—data, models, orchestration, evaluation, deployment, and governance—and understands how to make them reusable, reliable, and scalable. 

You will define the technical backbone for how teams experiment, deploy, and operate AI: from LLM-powered applications and agentic systems to classical ML, analytics, and decision intelligence. This is a hands-on, high-leverage role with broad architectural influence. 

RESPONSIBILITIES  

• • Architect and own the Data & AI platform—covering ingestion, feature pipelines, model development, LLM orchestration, evaluation, deployment, and monitoring. 
  • Design scalable GenAI and agentic architectures, including RAG pipelines, tool-using agents, multimodal systems, and hybrid ML + LLM solutions. 
  • Establish platform standards for experimentation, model evaluation, versioning, CI/CD, and production readiness across teams. 
  • Enable fast, safe innovation by creating reusable components, SDKs, templates, and internal tooling for data scientists, ML engineers, and product teams. 
  • Drive build vs. buy decisions for AI platforms, cloud services, vector databases, and orchestration frameworks with a strong cost, scalability, and flexibility lens. 
  • Partner closely with Data Science, Engineering, Product, and Analytics leaders to translate business needs into durable platform capabilities. 
  • Embed responsible AI practices into platform design—privacy, security, auditability, and human-in-the-loop evaluation. 
  • Act as a technical north star—reviewing designs, unblocking complex problems, and mentoring senior engineers across the org. 
  • A Lead engineer who thinks in systems, not just solutions. 
  • Equally comfortable designing architecture, writing production code, and reviewing others’ designs. 
  • Deeply pragmatic—you care about elegance, but you care more about reliability, adoption, and impact. 
  • Someone who has taken AI systems from research or prototype to real users at scale and learned the hard lessons. 

Qualifications

• • • Platforms & Infrastructure: Cloud-native architectures (AWS, GCP, Azure) 
    • Kubernetes, Docker, CI/CD, infrastructure-as-code 
    • Vector databases, feature stores, workflow orchestration 
    • Data & MLOps: Data pipelines, model lifecycle management, monitoring, experimentation 
    • Offline and online evaluation, A/B testing, human-in-the-loop systems 
    • AI / ML / GenAI: LLMs, RAG systems, agentic frameworks, prompt and model evaluation 
    • Build ecosystem for fine-tuning, hybrid ML + LLM architectures, NLP, multimodal systems 
    • 10+ years of experience across data engineering, ML/AI engineering, or platform engineering. 
    • Proven ownership of large-scale, production AI platforms used by multiple teams or products. 
    • Strong foundation in software engineering (Python-centric, APIs, microservices, distributed systems). 
    • Experience supporting consumer-scale or enterprise-scale AI products. 
    • Prior work on AI Centers of Excellence or shared AI platforms. 
    • Background in retail, digital products, supply chain, or customer-facing AI systems. 

The base salary range for this position is $180,000-$225,000 per year which represents the current range for the base salary for this exempt position. Please note that actual salaries will vary based on factors including but not limited to location, experience, and performance. As such, on occasion and when applicable, there is the possibility that the final, agreed-upon base salary may be outside of the upper end of the range. Please also note the range listed is just one component of the company’s total rewards package for exempt employees. Other rewards may include performance bonuses, long term incentives, a PTO policy, and many other progressive benefits.