Senior AI Engieer - Voice & Agentic Systems

Xebia is a global AI-first, digital transformation, and engineering partner.

With over 25 years of experience and a team of 5,000 professionals across 16 countries, we help organizations design and build scalable products, platforms, and data-driven solutions.

We specialize in Artificial Intelligence, Data and Cloud, Intelligent Automation, and Digital Products, combining deep technical expertise with a strong focus on engineering excellence and a people-first culture.

In the CEE region, we’re a team of nearly 1,000 experts delivering modern applications, data platforms, and AI solutions for clients such as Millennium, ING, Play, Edenred, Arabian Drilling, Fed Ex, Leroy Merlin, Truecaller, Volotea, Schmitz Cargobull, and many, many more. We work with leading technologies including AWS, Azure, GCP, Databricks, and Snowflake, and combine strong engineering culture with a consulting mindset and a continuous focus on growth and knowledge sharing.

We are looking for a Senior AI Engineer to join a product team building a voice-first AI agent that allows users to interact through natural spoken conversations. The agent reasons, uses tools, and takes actions in real time, with the product currently in active development and its architecture and product direction still evolving.

This is a hands‑on engineering role covering the full voice‑agent stack, from real‑time communication and speech processing to agent orchestration, tool use, memory, and backend integrations. You will have significant influence over both the technical architecture and product decisions, working closely with product, design, and a small engineering team.

• designing and building agent workflows using Lang Graph, including state management, tool and function calling, multi-step reasoning, memory, error recovery, and human handover,
• defining how the agent makes decisions during live conversations where latency and interruptions are critical,
• building and maintaining the backend integrations that allow the agent to take actions,
• designing reliable agent workflows that can operate in real-world production environments.

• building and tuning real‑time voice pipelines using technologies such as Pipecat, Live Kit Agents, or similar,
• working with streaming STT, TTS, voice activity detection, turn‑taking, and interruption handling,
• improving conversation quality through end‑of‑turn detection, barge‑in handling, filler and back‑channeling, and graceful error recovery,
• measuring and reducing end-to-end latency across the voice and agent pipeline,
• ensuring reliable voice interactions under real‑world network conditions.

• shaping the overall system architecture and making build‑vs‑buy decisions for models, speech technologies, and other components,
• building evaluation into the development workflow through conversation‑level test sets, regression suites, LLM‑as‑judge approaches, and latency and quality metrics,
• implementing observability and tracing using tools such as Langfuse, Lang Smith, or similar solutions,
• diagnosing production issues through traces, metrics, and real user sessions,
• applying strong engineering practices including code reviews, automated testing, CI/CD, documentation, and maintainable design.

• translating user needs and product goals into practical technical proposals,
• challenging assumptions and suggesting alternative approaches when they can improve the user experience,
• prototyping ideas quickly and hardening successful approaches for production,
• communicating technical trade‑offs clearly to both technical and non‑technical stakeholders,
• contributing to regular in‑person team sessions for planning, design, and technical reviews.

• proven…