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Senior AI Engineer - Lead Agent-Native Architecture

Explore Group • Czechia
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AI Summary

Lead next-gen AI product systems, define agent-native architecture, build autonomous LLM workflows. Collaborate with product teams to deliver AI-driven features end-to-end.

Key Highlights
Define agent-native architecture standards
Build automated context-infrastructure layers
Design multi-step autonomous LLM workflows
Key Responsibilities
Lead architectural design for agent-native systems
Develop self-healing workflows and multi-step LLM reasoning features
Prototype 0-to-1 ideas quickly, balancing trade-offs around latency, cost, reliability, and hallucinations
Technical Skills Required
Python Kotlin LLMs
Benefits & Perks
Relocation package available
Nice to Have
Previous experience as a founding engineer or building agentic multi-step systems from scratch

Job Description


Staff AI Engineer

Location: Hybrid (Prague / Brno, Czechia) + RELOCATION PACKAGE AVAILABLE

Type: Permanent

Stack: Python, Kotlin, LLMs, Pydantic AI, AWS, Kubernetes


About the Role

We are seeking a Staff AI Engineer to lead the architecture of next-generation, AI-native product systems. In this role, you will define agent-native architecture standards, build automated context-infrastructure layers, and design multi-step autonomous LLM workflows (spanning tool use, memory, and orchestration).

You will work alongside product and design teams to take complex AI-driven features end-to-end—moving from initial idea to validated production deployment at speed.


Key Responsibilities

  • Lead the architectural design for agent-native systems, clear API contracts, and context management layers for production AI workflows.
  • Develop self-healing workflows, multi-step LLM reasoning features, and systematic optimizations for AI-driven code reviews.
  • Build and evolve high-scale backend services using Python, Kotlin, or Java alongside event-driven architecture.
  • Prototype 0-to-1 ideas quickly, balancing trade-offs around latency, cost, reliability, and hallucinations in production LLM applications.


Requirements

  • 6–10+ years of core software engineering experience with strong backend foundation in Python, Kotlin, or Java.
  • Proven hands-on experience deploying LLM features into real products (prompt design, evaluations, context management, orchestration).
  • Solid understanding of distributed systems and event-driven architectures (queues, async processing, service-to-service communication).
  • Active daily user of modern AI development tools and agentic workflows.
  • Strong Plus: Previous experience as a founding engineer, startup founder, or building agentic multi-step systems from scratch.

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