Verbit

We are looking for a Senior Python Backend Engineer to join our Legal Tech engineering team and help build the next generation of AI-driven litigation ecosystem. This role combines top-tier backend engineering, cloud architecture, and cutting-edge LLM/AI innovation.

You’ll build high-scale, secure, multi-tenant services that turn our real-time transcription engine into AI-powered workflows and assistants used by legal teams. The role offers real ownership and chances to lead initiatives, while giving you space to grow your skills in AI development and modern dev-AI tools — all within a supportive, collaborative team.

This role is for people who bring passion, curiosity, and a genuine drive to build something meaningful as part of a strong, mission-driven team.

This is a remote position based in Ukraine. Candidates must have full professional proficiency in English.

What makes Verbit unique?
Verbit turns speech into impact. Our team of 250 professionals builds AI-driven solutions that help the world’s leading organizations get real value from their audio and video content. We serve high-end customers across the Legal, Media and Education markets with a next-generation verbal-intelligence platform that brings AI into the core of their workflows.

Our in-house technology combines advanced LLMs, GenAI capabilities and speech AI to power everything from legal-tech automation and real-time insights to intelligent media and learning workflows. Beyond transcription or accessibility, Verbit provides actionable intelligence: smart summaries, analytics, search, knowledge extraction, legal-deposition insights and more.

With more than 3,000 global customers relying on Verbit — including top law firms, universities, enterprises and media organizations — we’re building the future of how speech data is processed, understood and used.

     If you want to join our journey, you’ll need:

• 7+ years of hands-on backend development experience in a high-scale production environment
• Strong proficiency with Python, REST APIs and Cloud (e.g. AWS, GCP)
• Strong experience designing and building distributed, cloud-native microservices
• Experience with event-driven architectures and asynchronous processing
• Solid understanding of system design, scalability, availability, and performance optimization
  Practical experience using AI-powered development tools (e.g., Cursor, Claude Code)
• A significant advantage if you have practical experience with AI infra, such as: RAG, Agentic frameworks, Langfuse, LiteLLM
  Ability to take ownership and drive projects end-to-end, working proactively and independently and as a team in a fast-moving environment

• Good communication skills and teamwork
  Ability to work efficiently both individually and within a team

   

  It will be even better if you have:

• Formal education in relevant fields (CS, Math, Electrical Engineering etc.)
• Experience with large scale SaaS solutions
• Ability to integrate AI/LLM features into backend services (e.g., prompting, embeddings, RAG pipelines, fine-tuning)

We are seeking a skilled ML/AI Engineer to join our team and deliver cutting-edge ML/AI models in the ASR domain and legal insights more broadly. The core of this role is building, deploying, and serving ML models in production. 

A key part of this role is speech engineering — prior ASR/speech experience is not a must, but a willingness to learn and grow into this domain is essential. Experience with LLM-based solutions and agentic flows is an advantage, not a requirement. 

What you’ll do: 

• Build, deploy, and serve ML models in production — the core of the role — optimizing inference performance, latency, and efficient GPU utilization. 
• Support and extend our speech solutions, including 3rd-party ASR integrations and self-hosted ML models. 
• Evaluate and optimize key ASR/ML metrics such as WER, latency, F1 score, EER, and DER. 
• Secondary: Integrate LLMs and agentic flows into production solutions where they add value, including fine-tuning existing models. 

What you’ll bring: 

Core (required): 

• Solid background in machine/deep learning, with 4+ years of experience. 
• Strong Python skills and experience working in Linux environments. 
• Familiarity with deep learning libraries (e.g., PyTorch, TensorFlow) and training workflows. 
• Experience with MLOps pipelines and serving/deploying models in production. 
• Experience optimizing models for inference, including GPU acceleration. 
• Experience with Docker, gRPC, and serverless / micro-services architectures on cloud infrastructure (AWS/GCP/Azure). 
• Experience with real-time / streaming systems and low-latency processing (e.g. streaming pipelines, live sessions). 

Nice to have (secondary / optional): 

• Experience building and productizing agentic flows and AI-driven solutions (1+ year). 
• Familiarity with LLM / agent orchestration frameworks such as CrewAI, AWS Bedrock, Temporal, AgentCore, or LiteLLM. 
• Prior ASR / speech experience — not required; willingness to learn this domain is what matters most.