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Senior AI Platform Engineer
·Israel
HybridFull-timeAI EngineeringFraud PreventionIdentity VerificationeCommerce
Own shared AI infrastructure, agentic workflows, backend architecture, and data foundations for customer-facing commerce products. Build reliable LLM capabilities and mentor engineers across the organization.
Responsibilities
- Own and evolve shared AI infrastructure, including agentic workflows, LLM integrations, observability, and guardrails
- Build and deploy AI-driven capabilities using LangChain, LangFuse, and AWS Bedrock
- Set technical direction for backend services, data pipelines, and API patterns
- Design resilient data-access patterns across Snowflake, Elasticsearch, Kafka, Redis, and MySQL
- Ensure platform scalability, reliability, security, cost efficiency, and developer experience
- Mentor engineers in backend engineering, AI engineering, and system design
- Collaborate with product, design, and customer-facing teams to deliver well-scoped solutions
Requirements
- 6+ years of backend engineering experience
- Strong Node.js and TypeScript expertise
- Production experience building or integrating LLM-powered features or agentic workflows
- Experience with distributed systems and event-driven architectures
- Experience with Kafka, Redis, Elasticsearch, MySQL, and Snowflake
- Familiarity with cloud-native environments; AWS experience is advantageous
- Ability to design scalable, resilient, and maintainable systems
- Experience building customer-facing products with product managers and designers
- Strong communication and stakeholder-alignment skills
- Ability to own complex initiatives with minimal oversight
Nice to have
- Experience with LangChain, LangGraph, LangFuse, or similar tools
- Experience with AWS Bedrock or other LLM provider APIs
- Experience designing AI evaluation frameworks
- Familiarity with MCP or coding-agent tools
- Experience with React, Next.js, or micro-frontend architectures
- Python knowledge for AI or data workflows
Benefits
- RSU offerings
- Learning and development programs focused on AI tools
- Hybrid work model with at least three office days per week near company hubs
- 4.5-day work weeks
- Team outings and cultural celebrations