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Staff Backend Engineer, AI Platform - 100% Remote - EMEA

Hostaway

Remote · Austria Contract Lead 2d ago

About the role

Overview

In this Staff Engineer role, you own the architecture and technical direction of Hostaway’s AI Platform. You will lead the design and implementation of a multi-agent system that powers AI features across the product, ensuring reliability, observability, and scale. You’ll collaborate with product, design, and engineering teams to drive cross-team adoption and deliver AI‑powered experiences for 50,000+ property managers and their guests. This is a high‑autonomy, high‑impact position at a fast‑growing, valuation‑rich company. You’ll shape core infrastructure, mentor engineers, and set global standards for AI capability delivery.

Responsibilities

  • Own the AI Platform architecture and technical vision for the multi-agent system (agent delegator, sub‑agents, config service, LLM gateway, evaluation framework, conversation history, observability)
  • Build production‑grade AI infrastructure and core services for reliable, versioned, observable AI features
  • Define evaluation, quality gates, prompt comparison workflows, hallucination detection, and CI/CD integration for trustworthy features
  • Shape LLM gateway strategy including provider failover, model routing, cost tracking, and rate limiting
  • Drive cross‑team adoption by publishing internal blueprints and integration patterns for specialized agents
  • Influence engineering‑wide practices related to prompt engineering, tooling, observability, and agent testing
  • Mentor engineers through code reviews, architectural guidance, and hands‑on pairing

Requirements

  • 8+ years of software engineering experience, with at least 2 years at Staff level
  • Deep Python expertise and production‑grade Python services
  • Production experience with LLM‑based systems and operational realities (prompt/versioning, evaluation, cost management, observability, failure modes)
  • Familiarity with modern AI tooling (PydanticAI, LangChain, LangGraph, LiteLLM, Langfuse, Phoenix, MLflow) or comparable tools
  • Multi‑agent architecture experience is a strong plus
  • Comfort operating across a polyglot stack (Python, Go, PHP, React)
  • Infrastructure fluency (AWS, Kubernetes, CI/CD)
  • Cross‑team influence and ability to drive platform adoption

Tasks (Aufgaben)

  • 8+ years of software engineering experience
  • Deep Python expertise
  • Production experience with LLM‑based systems
  • Strong architectural instincts
  • Familiarity with AI tooling ecosystems (e.g., LangChain, Langfuse, MLflow)
  • Experience with multi‑agent architectures is a plus
  • Infrastructure fluency (AWS, Kubernetes, CI/CD)
  • Cross‑team influence and ability to drive platform adoption

Benefits & Central Requirements (Zentrale Anforderungen)

  • 100% Remote
  • Equity
  • Professional Growth
  • Annual Paid Leave
  • Geographic Specific Benefits
  • Dynamic Team Culture

Requirements

  • 8+ years of software engineering experience
  • Deep Python expertise
  • Production experience with LLM-based systems
  • Strong architectural instincts
  • Familiarity with AI tooling ecosystems (e.g., LangChain, Langfuse, MLflow)
  • Infrastructure fluency (AWS, Kubernetes, CI/CD)
  • Cross-team influence and ability to drive platform adoption

Responsibilities

  • Own the AI Platform architecture and technical vision for the multi-agent system (agent delegator, sub-agents, config service, LLM gateway, evaluation framework, conversation history, observability)
  • Build production-grade AI infrastructure and core services for reliable, versioned, observable AI features
  • Define evaluation, quality gates, prompt comparison workflows, hallucination detection, and CI/CD integration for trustworthy features
  • Shape LLM gateway strategy including provider failover, model routing, cost tracking, and rate limiting
  • Drive cross-team adoption by publishing internal blueprints and integration patterns for specialized agents
  • Influence engineering-wide practices related to prompt engineering, tooling, observability, and agent testing
  • Mentor engineers through code reviews, architectural guidance, and hands-on pairing

Benefits

EquityProfessional GrowthAnnual Paid LeaveGeographic Specific BenefitsDynamic Team Culture

Skills

AWSCI/CDGoKubernetesLangChainLangfuseLiteLLMLLMMLflowPydanticAIPHPPythonReact

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