Remote job
Remote confirmedAI Engineer – Agentic Systems (Voice) (m/f/d)
Acto
Job briefing
Read from the posting and checked against our job index
- Apply from
- Germany
- Work model
- Fully remote
- Full posting text checked
- Salary
- Not stated
- Level
- Senior
Your tasks
- Design and optimize LLM-powered agentic workflows for chat, meeting preparation, and recommendations
- Build agents that interact with external APIs, databases, and environments
- Advance real-time voice pipelines for transcription, speech synthesis, and dialogue management
- Integrate retrieval, long-term memory, and state tracking into agent architectures
- Deploy agents in production and evaluate their performance, correctness, latency, and hallucination rates
- OpenAI
- Claude
- Mistral
- LangChain
- LangGraph
- Python
- Hugging Face
- PyTorch
- Ray
- Coval
What they expect
Required skills
- Proven hands-on experience building voice agents in production and working with ASR, TTS, or real-time and streaming voice pipelines
- Strong experience building with LLMs
- Familiarity with agentic frameworks such as LangChain or LangGraph
- Proficiency in Python and experience with modern ML tooling
- Experience with tool integration, API calls, memory and state management, or SQL query generation
- Experience with simulation-based testing and evaluation of conversational and voice agents
Mindset
- Comfort working in an iterative, fast-paced product environment
- Motivation to help a small team level up
Good to know
- Listed with us since
- November 4, 2026
- Benefits in the posting
- 30 days of vacation, Wellhub membership, Choice of Mac or Windows hardware, Regular team events, Ownership and autonomy to make impactful decisions
Before you apply
These terms appear word for word in the posting. If you have these skills, they belong in your CV too.
- voice agents
- LangGraph
- Python
- simulation-based testing
- Hugging Face
- tool integration
Generated automatically by nomado24 from the posting and our index. Not an employer statement. The original posting is authoritative.
Job description
Your Role
We are growing our Agents team and looking for an experienced AI Engineer (m/f/d) to help build the next generation of agentic AI systems powered by Large Language Models (LLMs) . Today the team is small and tight-knit, and every hire meaningfully shapes what we build and how we build it.
You will work across our full agentic surface: chat, meeting preparation, recommendations, and voice . This is a hands-on role at the intersection of reasoning, tool-use, and memory, designing intelligent agents that operate in complex environments, interact with APIs and structured data, and drive real-world outcomes. It goes well beyond prompt engineering: you will build robust decision pipelines and ship product-ready agents across both text and voice modalities .
Proven experience building voice agents is an important requirement for this role. Voice is one of the most exciting frontiers of our product, and we want someone who has done it to help the whole team excel there. That said, this is not a voice-only role: you will contribute across the Intelligence Layer, and your voice background will be a force multiplier for everything we build together.
Your Mission
- Design & Optimize Workflows: Design, implement, and optimize agentic workflows using LLMs across chat, meeting prep, and recommendations.
- Build Tool-Using Agents: Create agents that interact with external APIs, databases, and environments.
- Advance our Voice Agents: Push our voice-enabled agents forward, including pipeline design for real time conversation, transcription (ASR), speech synthesis (TTS), turn-taking, and dialogue management, with a focus on low latency and reliability.
- Integrate Memory & State: Implement retrieval, long-term memory , and state tracking into agent architectures.
- Deploy in Production: Collaborate with product teams to deploy agents in production and keep them healthy.
- Evaluate & Improve: Design and run experiments to evaluate agent performance, correctness, latency, and hallucination rates.
- Translate Product Needs: Turn high-level product requirements into scalable, testable agentic features.
Your profile: What you need to succeed
- Voice AI (important requirement): Proven, hands-on experience building voice agents in production and working with ASR , TTS , or real-time/streaming voice pipelines. Voice is a core focus of this hire, and we expect you to bring real depth here.
- LLM Expertise: Strong experience building with LLMs (e.g., OpenAI, Claude, Mistral, open-source models).
- Agentic Frameworks: Familiarity with agentic frameworks (e.g. LangChain, LangGraph).
- Programming Proficiency: Proficient in Python and modern ML tooling (e.g., Hugging Face, PyTorch, Ray, etc.).
- Tool Integration: Experience with tool integration , calling APIs, managing memory/state, or SQL query generation.
- Simulation-Based Testing: Experience with simulation-based testing and evaluation of conversational and voice agents (e.g. Coval , Bluejay ), used to measure agent performance, correctness, and regressions at scale.
- Startup Mindset: Comfortable in an iterative, fast-paced product environment, and energized by helping a small team level up.
Why Acto?
- Development Opportunities : Steep development opportunities without entrenched hierarchies.
- Culture: We are an ambitious team that wants to achieve a lot with Acto, but we don't take ourselves too seriously and like to have fun together, be it working together or at regular team events.
- Flexibility: Enjoy a flexible work schedule and a remote set up with the option to work from our Berlin Office.
- Health & work-life balance: Enjoy 30 days of vacation and an attractive Wellhub membership.
- Ownership: Whether you are an intern or a full-time acto-naut, Acto instills a deep sense of ownership, where every team member is entrusted with meaningful responsibilities and the autonomy to make impactful decisions.
- Equipment: You will receive a state-of-the-art hardware setup with a choice between Mac and Windows.
This role is provided by an external source. Applications are handled on the source website.
