דרושים Backend & AI Engineer בתל אביב

What You’ll Do

● Lead Engineering Excellence: Own the backend and infrastructure stack across services, pipelines, and AI components.

● Develop and Deploy: Design and implement features using TypeScript (NestJS), Python, and Java across microservices running on AWS and Azure,

orchestrated via Kubernetes.

● Engineer Data Systems: Build scalable, production-grade pipelines. Experience with Prefect is a strong plus.

● Innovate with AI: Design and build autonomous agents, RAG pipelines, and backend systems that interact with LLMs at scale. You’ll work with

(and sometimes create) prompting frameworks, implement Model Context Protocols (MCP), and develop AI-native logic that operates in real production

environments.

● Own the Delivery: Deliver end-to-end features with full ownership, including testing, deployment, and observability.

● Build for Scale: Solve real-world problems in logistics with engineering that adapts to complex business demands.

About You

● Education: B.Sc in Computer Science, Engineering, Mathematics—or equivalent hands-on experience

● Backend Expertise: Strong experience in Node.js, TypeScript, Python/Java/C#, microservices, and distributed systems

● Cloud Native: Hands-on experience deploying and operating services in AWS and/or Azure cloud environments

● Data Engineering: Familiarity with batch and stream processing, data orchestration tools (Prefect is a big plus)

● AI Engineering: Comfortable working with modern AI tools, especially those involving prompting, LLMs, and agents

● MCP Knowledge: Advantage for candidates who’ve worked with Model Context Protocols (MCPs) or similar LLM infrastructure

● Database Proficiency: Solid experience with relational and NoSQL databases in production

● CI/CD: Familiar with continuous integration and deployment pipelines

● Soft Skills: Fast learner, strong communicator, excellent problem-solver, highly accountable and proactive

● Bonus Points:

○ Security clearance (active military classification)

○ Experience in big data environments

○ Experience working with

distributed or remote teams