Sr. AI Backend & Data Engineer
Pendo- Compensation
- up to $200k Published range
- Location
- Hybrid - Herzliya, Tel Aviv, Israel Remote eligibility
- Employment
- Full-time Senior
About the job
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. The team owns the full stack from distributed data pipelines and backend services to ML and AI-powered capabilities. Agentic AI development is a core part of how we increase engineering velocity.
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.
What You Will Build
- AI-Native Systems Development: Design, build, and own scalable data and ML pipelines, backend services, and AI-powered capabilities.
- Daily Shipping: Decompose complex work into safely mergeable increments and ship daily, using feature flags, canary releases, and rollback architecture.
- AI-Augmented Engineering Workflow: Leverage AI-assisted development tooling as a core workflow multiplier.
- End-to-End Ownership: Own work from design through production deployment, operational monitoring, and business impact measurement.
- Architectural Decision-Making: Make pragmatic, timely architectural choices and document decisions in lightweight ADRs.
- Cross-Functional Collaboration: Partner with product, design, infrastructure, and GTM teams.
What You Bring
Required: 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. Active use of AI-assisted development tooling. 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.
Preferred: Experience shipping ML-Ops powered systems in production, distributed data technologies (e.g., Parquet, Athena), and making/documenting architectural decisions autonomously (ADRs).
Skills & tags
Compare the essentials before you leave: pay, remote scope, employment type, source, and the employer apply destination.