דרושים » תוכנה » AI Native Senior Developer & Architect

Requirements:
6+ years of experience as a Full-Stack or Backend Engineer, with a strong track record building and scaling production systems.
Deep Node.js and TypeScript expertise - you know the ecosystem well and write clean, maintainable code.
Solid React and modern frontend skills: state management, performance optimization, and component architecture.
Hands-on experience with microservice architecture and distributed systems, and a clear sense of the trade-offs involved.
Cloud-native fluency: Docker, Kubernetes, CI/CD pipelines, and hands on experience with GCP, AWS, or Azure.
AI-Driven Development: Daily use of AI coding assistants (Cursor, Copilot, Claude, etc.) with a clear perspective on how to maximize their potential
Hands-on experience building with LLM APIs (prompt engineering, tool/function calling, agent design, or RAG pipelines) and familiarity with MCP (Model Context Protocol).
Comfortable with RESTful and event-driven APIs, TDD, security best practices, and clean code principles.

Requirements:
8+ years of experience designing and building large-scale distributed systems.
Proven expertise in complex data architecture design (schema design, indexing, caching, governance).
Strong backend development experience (Go, Java, or similar).
Deep experience with modern data storage technologies (PostgreSQL, MongoDB, Elasticsearch, Kafka, ClickHouse, or similar).
Strong understanding of microservices, event-driven systems, and SaaS architecture patterns.
Hands-on experience in cloud-native environments (Docker, Kubernetes, AWS/GCP/Azure).
Experience leading architectural alignment across multiple engineering teams.
Excellent communication, documentation, and cross-functional leadership skills.
Strong understanding of modern AI-driven architectures, including LLM orchestration, tool execution frameworks, and runtime safety considerations.
Ability to design AI-enabled systems with performance, isolation, and resilience at scale.
B.Sc. in Computer Science or equivalent experience (advanced degree or elite technical unit background - advantage).

Requirements:
8+ years of experience building and operating large-scale data and AI systems, with 5+ years in architecture or platform leadership roles driving technical direction across multiple teams.
Demonstrated experience defining and executing architectural vision in complex, multi-team environments, including setting standards, leading design reviews, and influencing long-term roadmaps.
Deep expertise in cloud-native distributed systems (GCP, AWS, or Azure), including Kubernetes-based infrastructure (e.g., GKE), scalable storage and compute, reliability, and security at scale.
Strong command of modern data architectures (data lake, lakehouse, warehouse) and large-scale analytics platforms (e.g., BigQuery, Databricks), including data lifecycle, metadata, and governance strategy.
Proven experience designing internal data and ML platforms that enable reproducible experimentation, self-serve workflows, and efficient research-to-production transitions.
Experience architecting end-to-end ML lifecycle systems, including training infrastructure, experiment tracking, versioning, CI/CD for ML, deployment patterns (batch/online), and monitoring across MLOps platforms (e.g., ClearML, RunAI, or equivalents).
Strong understanding of security, privacy, and compliance requirements in regulated environments, including fine-grained access control, auditing, and data protection best practices.
Desired personal traits:
You want to make an impact on humankind
You prioritize We over I
You enjoy getting things done and striving for excellence
You collaborate effectively with people of diverse backgrounds and cultures
You have a growth mindset
You are candid, authentic, and transparent.