AI/ML Engineer, Docplanner

• 2+ years hands-on experience with LLMs (OpenAI or similar, open-source models)
• Strong knowledge in prompt engineering and LLM optimization strategies
• Experience in evaluating LLMs, designing and running evaluation frameworks, creating test datasets, and defining success metrics
• Familiarity with automated testing pipelines, building CI/CD-integrated eval systems that run on every prompt change
• Experience in multi-agent architecture, from design to development of orchestration of complex LLM systems
• Good understanding of transformer architectures and proficiency in LLM frameworks such as LangChain, LlamaIndex, or similar frameworks
• Proficiency in Python
• Experience with RAG pipelines and vector databases
• Experience in cross-functional teams, ability to work in fast-moving environments where you own outcomes, not just tasks. You're comfortable with ambiguity and excited by the challenge of figuring things out

Desirable

• We are looking for an innovative AI/LLM Engineer to drive the advancement of our conversational AI capabilities
• You'll join our Tech&Product team as an AI/LLM Engineer, focusing on prompt engineering, multi-agent orchestration, automated testing, and deploying integrations in production with LLM systems
• You'll work closely with Backend Engineers to deliver world-class AI experiences to end users
• Design, optimize, and version prompts for production voice and chat LLM applications
• Architect and orchestrate multi-agent systems for complex conversations
• Build automated testing and validation frameworks for LLM outputs
• Implement prompt versioning, storage, and retrieval systems
• Collaborate with Backend Engineers to deploy and scale LLM-based systems
• Integrate LLMs with communication APIs (Twilio, WhatsApp, ElevenLabs)
• Implement RAG (Retrieval-Augmented Generation) solutions and vector search for multilingual environments
• Monitor performance metrics and conversation quality
• Research and prototype multi-agent frameworks (open-source and commercial)
• Experiment with cutting-edge conversational AI and real-time speech processing techniques
• Contribute to evolving the team's LLMOps best practices
• Continuously improve conversational quality, RAG pipelines, and reduce latency

• HR interview – a friendly chat to get to know you, your motivations, and tell you more about Tuotempo, our culture, and the team
• Technical interview – a deep-dive with our Tech Managers, including practical discussions or small exercises focused on LLMs, multi-agent systems, prompt design, and evaluation workflows
• Functional interview — a conversation with our Product Managers to understand how you collaborate cross-functionally and to align on the AI product domain