Avaloq

AI Software Engineer

11 Tage alt

Angaben zum Job

Avaloq
Firma Avaloq
Kategorie IT, Ingenieurswesen
Pensum 100%
Lohn (geschätzt) CHF 88'000 – 112'000 / Jahr
Home Office Homeoffice möglich
Benefits Flexible Arbeitszeiten
Einsatzort Zurich

Job-Inhalt

Job Description

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

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

Bewerben

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