Summary
✨ AI‑Generated
A technology company is seeking an experienced engineer to develop AI-enabled distributed systems. The role involves designing cloud architectures, building intelligent applications, and working across backend and full-stack technologies.
Highlights
Advanced engineering role combining large-scale software development with applied AI, cloud-native architectures, and autonomous technical ownership.
Description
We are looking for a Software Engineer who operates at the intersection of high-scale full-stack engineering and cutting-edge Applied AI.
Requirements
7+ years of backend or full-stack engineering experience, including 2+ years building production-grade agentic systems in distributed environmentsStrong proficiency in Python (preferred) or TypeScript/Go/Rust, with the ability to transition to PythonHands-on experience with agentic frameworks such as LangChain, LangGraph, CrewAI, DeepAgents, OpenClaw, Hermes, or equivalentProven expertise in designing cloud-native, event-driven architectures using AWS, Kubernetes, Terraform, CI/CD, GraphQL or REST APIs, and messaging systems (SQS/SNS)Experience with PostgreSQL, DynamoDB, MongoDB, and preferably vector databasesFamiliarity with AI-native development tools such as Claude Code, Cursor, or CopilotExcellent communication skills and the ability to work independently in a highly autonomous environment
Will be a plus
Experience with React, Next.js, or similar frontend technologies
What we offer
Help and support from our caring HR team15 working days of annual paid leaveThe exchange of experience and work with talented colleaguesMobilization reservation available upon successful completion of the probation period (for Ukrainian colleagues)Last but not least - valuable compensation for your efforts
Responsibilities
Architect & Build: Design and deliver agentic workflows and scalable microservices, primarily using Python, within a distributed system architectureAI Integration: Lead the integration of Generative AI capabilities, including LLM APIs, RAG pipelines, and agentic workflows into our production systemsAgentic Operations & Observability: Implement operational practices, observability, and autonomous monitors (e.g., detecting intelligence drift or hallucinations) to ensure AI reliability in productionElevate Engineering: Drive overall engineering quality and speed by implementing AI-SDLC practices, ensuring high standards through rigorous code reviews, test automation, and by establishing continuous, trace-based quality evaluation for all software and agentic componentsMentor & Innovate: Evaluate emerging AI tooling, mentor fellow engineers, and contribute directly to our technical roadmap and Agentic AI-SDLC and Production Operations
