Engineering Lead, ML Infrastructure + Data Engineering

Grid is seeking an Engineering Lead, ML Infrastructure + Data Engineering to build and scale our FinTech core. You’ll collaborate closely with business operations and the product engineering team to deliver reliable backend services, from automated ledger reconciliation to AI/ML model integration, across real-time and batch data pipelines. This leadership role combines hands-on engineering with strategic direction to support rapid growth and scale.

What youll do

• Lead a small backend engineering team to deliver mission-critical systems end to end.
• Provide infrastructure support for training and online inference to our AI/ML team.
• Design, develop and operate core data systems for ingestion, warehousing and analysis.
• Operate and scale internal treasury management APIs.
• Debug, quantify and minimize exceptions to improve reliability.
• Establish sustainable DevOps and FinOps practices, including monitoring and analytics.
• Champion new practices to enhance customer experience and enable exponential growth.
• Own projects from conception through delivery and ongoing optimization.

What Grid is looking for

• Extensive experience leading backend/infrastructure teams and delivering complex systems at scale.
• Proficiency with CI/CD and infrastructure as code (Terraform, Kubernetes, GitOps) for scalable deployment.
• Hands-on experience designing and operating real-time streaming and batch data pipelines (Pub/Sub, Dataflow, Spark) on GCP.
• Domain knowledge in FinTech/financial ledger systems with ledger reconciliation or related financial data workflows.
• Experience with Grid’s tech stack: GCP, Go, protobufs, MySQL.
• Experience integrating AI/ML models into production-grade backend services, including model serving, monitoring, and experimentation workflows.
• Strong CS fundamentals; degree in Computer Science or a related field is a plus.