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Senior AI Engineer

Pendo.io·ישראל·
במקום העבודהמשרה מלאהAI EngineeringEnterprise Software

Build and operate AI-integrated data systems, backend services, and production capabilities for an AI-native predictive analytics platform. Own solutions from architecture and implementation through deployment, monitoring, cost management, and business impact.

תחומי אחריות

  • Design, build, and own scalable data and ML pipelines, backend services, and AI-powered production capabilities.
  • Integrate AI and ML components as runtime dependencies in production decision-making systems.
  • Ship software in small, safely mergeable increments using feature flags, canary releases, and rollback strategies.
  • Use and evaluate AI-assisted development tools for code generation, testing, and architecture prototyping.
  • Own solutions through design, deployment, operational monitoring, cost efficiency, and business impact measurement.
  • Maintain CI/CD pipeline health and observability.
  • Make, document, and own pragmatic architectural decisions using lightweight ADRs.
  • Collaborate with product, design, infrastructure, and go-to-market teams to translate customer needs into technical solutions.

דרישות

  • At least 5 years of experience building and shipping production-grade backend and data systems in distributed cloud environments.
  • Production experience integrating AI, machine learning, LLM, or agent-based components into live workflows.
  • Active use of AI-assisted development tools such as Copilot, Cursor, or equivalent.
  • Strong backend development experience with Java and Spring Boot, Python, and/or Go.
  • Experience with relational and non-relational databases, data modeling, and query optimization.
  • Expertise in automated testing, CI/CD, and observability.
  • Ability to decompose complex work into incremental deliveries and ship safely on a frequent basis.
  • Ability to make pragmatic architectural decisions and balance reliability, cost, and delivery speed.

יתרון

  • Production MLOps experience, including model serving, monitoring, or retraining pipelines.
  • Experience with distributed data technologies such as Parquet, Athena, or similar query engines.
  • Experience documenting autonomous architectural decisions through ADRs or equivalent records.

רלוונטיות

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