Sr. AI Backend & Data Engineer

About the Team: This team builds an AI-native predictive analytics platform that embeds ML and AI-driven insights directly into production Go-To-Market workflows — powering real-time decisions at scale. The team owns the full stack from distributed data pipelines and backend services to ML and AI-powered capabilities that ship directly to customers. We are building toward a model where AI components are first-class runtime dependencies, not bolt-on features. Agentic AI development is a core part of how we increase engineering velocity and deliver customer value. This is a team that ships daily, iterates constantly, and treats speed as a capability to be deliberately improved. The Role: This is a high-ownership, builder-first Sr. Software Engineer role. You will design, build, and ship AI-integrated data systems from concept through production — owning outcomes end-to-end, including deployment, monitoring, cost, and business impact. We are seeking a candidate who views AI tooling as a fundamental force multiplier in their daily engineering process. This position is central to our transition into an AI-native function, requiring an individual capable of making decisive, pragmatic architectural choices on reversible matters to maintain momentum. We need an experienced builder of production-grade, data-centric systems who is obsessed with delivering customer value and possesses a deep, curious enthusiasm for the transformative potential of AI.

Responsibilities

Design, build, and own scalable data and ML pipelines, backend services, and AI-powered capabilities; Decompose complex work into safely mergeable increments and ship them daily; Leverage AI-assisted development tooling as a core workflow multiplier; Own work end-to-end from design through production deployment, monitoring, and business impact; Make pragmatic, timely architectural choices and document decisions; Partner with product, design, infrastructure, and GTM teams to translate customer and business needs into technical solutions

Requirements

5+ years building and shipping production-grade back end and data systems in distributed cloud environments (AWS and/or GCP); Hands-on AI/ML integration in production workflows (AI, LLM, or agent-based components in production runtime); Active use of AI-assisted development tooling (Copilot, Cursor, or equivalent) as a workflow multiplier; Strong back end expertise in Java (Spring Boot), Python, and/or Go; Hands-on experience with relational and non-relational databases, data modeling, and query optimization; Demonstrated expertise in automated testing, CI/CD, and observability; High-Velocity ownership in high-ownership, builder-first environments; Demonstrated ability to break work into small, safely mergeable increments and maintain strong delivery flow

Nice to have

Experience shipping ML-Ops powered systems in production (model serving, monitoring, retraining pipelines); Experience with distributed data technologies (e.g., Parquet, Athena, or similar query engines); Experience making and documenting architectural decisions autonomously (ADRs or equivalent lightweight decision records)