Senior AI Engieer - Voice & Agentic Systems
About this role
This role addresses the need to develop a sophisticated, voice-first AI agent capable of reasoning, tool use, and real-time action execution during spoken conversations. The team is focused on building a product where users interact with an AI through natural speech, requiring robust engineering across the entire voice-agent stack. This is a hands-on engineering opportunity where the individual will have substantial influence over both the technical architecture and product direction as the product evolves. The role exists to bring together expertise in complex agentic workflows, real-time voice processing, and production-grade system design to deliver a functional, reliable conversational AI product.
The successful candidate will be responsible for designing and implementing the core logic of the agent, focusing on agent engineering, voice pipeline tuning, and ensuring overall system quality. This involves making critical decisions regarding technology choices for models and speech technologies, while also translating user requirements into tangible technical solutions. It is ideal for an engineer who thrives at the intersection of deep technical implementation and product strategy, capable of moving from concept to production deployment.
This position is suited for an experienced engineer who has successfully shipped GenAI and agentic systems to end-users. The ideal candidate possesses a strong engineering foundation, a product sense, and the ability to communicate complex technical concepts clearly to diverse audiences.
What you will do
- Design and build agent workflows utilizing LangGraph, focusing on state management, tool calling, multi-step reasoning, memory, and error recovery.
- Define the decision-making logic for the agent during live conversations, prioritizing low latency and interruption handling.
- Develop and maintain the backend integrations necessary for the agent to execute real-world actions.
- Build and tune real-time voice pipelines using technologies like Pipecat or LiveKit Agents.
- Improve conversation quality by implementing mechanisms for end-of-turn detection, barge-in handling, and graceful error recovery.
- Measure and work to reduce latency across the entire voice and agent pipeline.
- Shape the overall system architecture and make build-vs-buy decisions for various AI and speech components.
- Implement observability and tracing solutions to diagnose production issues effectively.
What you need
- Demonstrated track record of deploying GenAI and agentic systems into production environments used by actual users is required.
- Possesses hands-on experience with LangGraph, including the design and execution of production workflows.
- Strong proficiency in Python, particularly in asynchronous programming and building production services like FastAPI applications.
- Possesses strong software engineering and system architecture skills, capable of designing systems end-to-end and making informed technical trade-offs.
- Requires senior or lead-level engineering experience with ownership over significant technical decisions.
- Must have a strong product sense and evidence of influencing product direction, not just implementation details.
- Needs a solid understanding of production-quality software development practices, including testing, observability, and reliability.
- Fluency in English is necessary for clear communication with both technical and non-technical stakeholders.
Nice to have
- Practical experience using AI-powered assistants (e.g., Claude Code, GitHub Copilot, Cursor) to improve productivity, quality, or decision-making in software delivery.
Benefits
- Work from the European Union region
Skills and tech stack
Questions candidates ask
What is the remote policy?
The job posting indicates that candidates must work from the European Union region. A work permit is required for this role.
What is the expected compensation?
The salary information is not provided in the job posting.
What is the primary technology stack for this role?
The tech stack includes LangGraph, Pipecat, LiveKit Agents, and cloud providers such as AWS, Azure, GCP, Databricks, and Snowflake.
What is the team structure like?
The role involves working closely with product, design, and a small engineering team, and participation in regular in-person team sessions is expected.
The application is on the official Poland and Middle-Eastern Europe careers page.
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