We are seeking a highly skilled, fast learner and well rounded, AI Software Engineer to join our AI innovation lab team. The ideal candidate will lead AI experiments and bring cutting-edge AI Agentic solutions from ideation to production.

The mission of Avaloq AI Lab is to improve operational efficiency and augment Back-to-Front Office user experiences, through the application of state-of-the-art AI technology. We work collaboratively with industry leaders to deliver responsible and impactful solutions. Our team develops products tailored to the banking sector, supporting a broad range of users including banking operations, software engineers, knowledge services teams, and relationship managers.

Your key tasks

• Lead AI experiments and develop solutions from ideation to production
• Collaborate with cross-functional teams to design and implement Agentic AI solutions
• Develop advanced prompts, multi-Agents architecture and tools
• Deploy and maintain LLM based solutions in production
• Optimize solutions for performance, cost, and scalability
• Stay up-to-date and evaluate the latest advancements in AI research and related regulations
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Qualifications

• At least B.Sc. degree in Computer Science, Engineering, or a related field
• Strong background in data science, statistics, and experimental thinking
• Understanding of data structures, algorithms, and software design principles
• Effective communication and collaboration skills
• Excellent analytical, coding, and debugging skills in Python
• At least 5 years of experience in Full-Stack Software Development
• At least 3 years of applied ML experience, with 2 years of experience with LLMs and Agents
• Proven track-record of deploying and maintaining AI models in production
• ML frameworks such as TensorFlow, PyTorch, Scikit-learn or similar
• RAG pipelines with vector stores (e.g., Chroma, Qdrant)
• Agent frameworks (e.g., LangChain, Google ADK, CrewAI)
• Cloud AI services e.g. AWS (SageMaker, Bedrock), Azure (AI Studio), GCP (Vertex AI)
• LLM & Agent Ops - experiment tracking tools, observability tools, evaluation pipelines, prompt engineering and maintenance tools
• Familiarity with containerization technologies (e.g. Docker) and container orchestration systems (e.g. Kubernetes)
• Micro-services and REST APIs