Lead Data Engineer & Modeler, AI - Hybrid

At Commerce, our mission is to empower businesses to innovate, grow, and thrive with our open, AI-driven commerce ecosystem. As the parent company of Big Commerce, Feedonomics, and Makeswift, we connect the tools and systems that power growth, enabling businesses to unlock the full potential of their data, deliver seamless and personalized experiences across every channel, and adapt swiftly to an ever-changing market.

We help businesses confidently solve complex commerce challenges so they can build smarter, adapt faster, and grow on their own terms.

Big Commerce is building the foundation for the next generation of AI-driven commerce. As a Lead AI Engineer, Platform & Infrastructure, you’ll define and scale the systems that make this transformation possible. This role sits at the intersection of data engineering, MLOps, and applied AI enablement, responsible for building the secure, scalable, and high-performance infrastructure that supports AI/ML use cases across the company.

• Partner with the Enterprise Architect and Principal Data Architect to design the company-wide AI/ML platform strategy across GCP and AWS.
• Build scalable systems for model training, evaluation, deployment, and monitoring.
• Define best practices for data ingestion, feature stores, vector databases, and model registries.
• Integrate AI workflows into existing analytics and product pipelines.

• Implement CI/CD for ML pipelines (MLOps) including model versioning, validation, and automated deployment.
• Ensure platform reliability, observability, and performance at enterprise scale.
• Manage GPU/TPU resources and optimize compute efficiency for training and inference workloads.
• Contribute to cost-optimization and security best practices across the AI infrastructure.

• Partner with data scientists, applied ML engineers, and product teams to translate model requirements into scalable architecture.
• Work closely with the data engineering team to ensure AI pipelines align with governance and data quality standards.
• Collaborate with software engineers to integrate AI services and APIs into production systems.

• Champion data and model governance, including lineage, reproducibility, and compliance (GDPR, SOC, ISO).
• Establish monitoring frameworks for model drift, bias detection, and ethical AI use.
• Build secure and transparent systems that support trust in AI-driven decisions.

• 7+ years in data or ML engineering, with experience designing production-grade AI infrastructure.
• Strong technical foundation in MLOps, data pipelines, and distributed systems.
• Hands‑on experience with:
  • Cloud AI platforms (Vertex AI, Sage Maker, Bedrock, or equivalent)
  • Orchestration frameworks (Airflow, Kubeflow, MLflow, or Metaflow)
  • Cloud data stacks (Big Query, Snowflake, GCS/S3, Terraform)
  • Model serving tools (FastAPI, Bento
    
    ML, Ray Serve, or Triton Inference Server)
• Proficient in Python, SQL, and Git-based CI/CD.
• Experience integrating LLMs and vector databases (e.g., Pinecone, FAISS, Weaviate, Vertex Matching Engine).
• Familiarity with Kubernetes, Docker, and Terraform for scalable deployment.
• Strong communication skills, able to partner across disciplines and simplify complex technical systems.

• The AI foundation powering every intelligent capability within Big Commerce — from predictive analytics to generative assistants.
• The tools and frameworks that enable product and engineering teams to build, test, and ship AI faster.
• The reliability, governance, and scalability of Big Commerce’s enterprise-wide AI ecosystem.

You’ll play a critical role in shaping how Big Commerce operationalizes AI — not just as a feature, but as a platform capability. You’ll join a collaborative, ambitious, and fast-evolving data organization dedicated to creating systems that enable intelligence at scale.

Pay Transparency Range: $116,000-$174,000

At Commerce, we believe that celebrating the unique histories, perspectives and abilities of every employee makes a difference for our company,…