Senior AI Platform Engineer

Technologies we use

About the project

Your responsibilities

• Develop and launch scalable conversational AI systems that operate across multiple channels, including chat, voice, email, and APIs
• Architect microservices and asynchronous systems for AI applications, ensuring high availability and performance
• Use Python to implement orchestration and decision logic - the control layer that manages tools, workflows, and system interactions
• Agentic Evaluation & Quality Gates: Design evaluation frameworks for autonomous agents tracking multi-step workflows, tool-calling accuracy, and session performance, integrating automated gates into CI/CD pipelines
• LLM-as-a-Judge & Testing Pipelines: Establish automated evaluation protocols utilizing LLM-as-a-judge patterns
• Optimize AI models through fine-tuning and LoRA integration, making data-driven decisions between different approaches (FT vs RAG)
• Work with data specialists to design pipelines for collecting, cleaning, and structuring information for AI agents
• Design CI/CD pipelines, container standards, and cloud strategies for infrastructure migrations, cost optimization, and high availability

Our requirements

• Strong background in Python, mainly for hooking up AI models, automating stuff, and handling orchestration logic
• 1–2 years of hands-on experience with Generative AI and large language models (LLMs)
• Practical experience in machine learning engineering: data preparation, working with vector databases in the cloud, and training/optimizing models
• Expertise in Agentic Evaluation: Hands-on experience designing evaluation frameworks for complex, multi-agent systems and evaluating reasoning traces, tool selection, and agentic workflows
• LLMOps & CI/CD Gate Design: Proven experience in building automated testing and evaluation gates within CI/CD pipelines for AI models
• Strong backend and frontend architecture experience
• Experience working with cloud platforms such as AWS, GCP, or Azure, including container orchestration and CI/CD pipelines
• Experience with agentic frameworks (LangChain, LangGraph) and multi-agent system design

Optional

• Comfort with ML frameworks such as TensorFlow, PyTorch, or Scikit-learn is a plus

What we offer

This is how we work on a project

Development opportunities we offer

Benefits