We are seeking a talented and motivated Agent OS Developer to join client’s team in designing and building the core infrastructure that powers intelligent agent-based systems. You will be instrumental in creating the operating system that orchestrates agent behaviors, manages workflows, and integrates with external tools and APIs. This is a unique opportunity to shape the next generation of computing where autonomous agents collaborate to solve complex tasks.
- Start Date: ASAP
- Contract Duration: 6 months (extension likely)
- Location: Remote, with possible occasional in person team sessions / workshops / gatherings (i.e. 1x quarter) likely to take place in Prague
- Languages: English fluent
- 10am -6pm CET. possibility of a wider overlap (flexibility) appreciated
Scope:
- Design and develop the Agent Operating System (Agent OS) to support multi-agent coordination, task planning, and execution.
- Implement core services such as memory, perception, planning, scheduling, environment modeling, and long-term state persistence.
- Develop abstractions and APIs that allow developers to define, manage, and deploy agents in dynamic environments.
- Integrate with LLMs, vector stores, toolchains, and third-party APIs to enable agent capabilities such as reasoning, code generation, and data analysis.
- Build agent lifecycle management tools, including initialization, state management, failure recovery, and inter-agent communication.
- Ensure the Agent OS is secure, scalable, fault-tolerant, and optimized for low-latency interactions.
- Collaborate with research, ML, and platform teams to test and iterate on features grounded in real-world use cases.
- Contribute to documentation, developer tooling, and best practices for building with Agent OS.
Requirements:
- Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related field.
- 4+ years of experience in systems-level development, distributed systems, or AI frameworks.
- Proficiency in Python, Rust, or Go. Experience with asynchronous programming and microservices architecture.
- Familiarity with agentic frameworks like LangChain, LangGraph, CrewAI, Autogen, ReAct, or bespoke task-oriented agents.
- Familiarity with patterns like Supervisor, Judge and multi-agent architecture
- Deep understanding of AI/ML infrastructure, including LLMs, embeddings, prompt orchestration, and vector databases.
- Experience with multi-agent systems, behavior trees, or reinforcement learning is a plus.
- Knowledge of containerization (Docker), orchestration (Kubernetes), and cloud platforms (AWS, GCP, Azure).