Senior Software Engineer AI applications

• Design and develop backend applications for data- and AI-driven products, mainly using Python.
• Build and maintain APIs, backend services, and distributed systems.
• Translate business and technical requirements into scalable and maintainable solutions.
• Design and discuss technical solutions together with engineers, architects, Product Owners, and other stakeholders.
• Challenge requirements and assumptions constructively and identify the best solution for a given business problem.
• Develop AI-enabled applications, such as RAG solutions, semantic search, knowledge assistants, and agentic workflows.
• Evaluate and adopt new AI technologies and quickly become productive with emerging tools and frameworks.
• Distinguish useful technologies from hype and assess whether a new technology actually brings value to the specific use case.
• Take ownership from concept to production, including development, deployment, operation, and continuous improvement.
• Work with Docker, Kubernetes/cloud platforms, CI/CD, and GitOps to deploy and operate applications.
• Participate in code reviews and collaborative Git workflows and ensure high-quality, clean, and maintainable code.
• Implement and improve monitoring, logging, tracing, and observability of production systems.
• Communicate technical concepts and trade-offs clearly to both technical and non-technical stakeholders.
• Work independently and drive technical topics forward without requiring detailed instructions.
• Mentor other engineers and potentially lead technical initiatives.

Must have

• 5+ years of professional software engineering experience, with a strong focus on backend development and Python for production grade systems
• Solid experience building backend services, APIs, and distributed systems
• Experience with containers and deployment technologies such as Docker, Kubernetes, or serverless platforms
• Good understanding of software architecture, clean code principles, and engineering best practices
• Experience working with Git, pull requests, code reviews, and collaborative development workflows
• Practical experience with CI/CD and GitOps concepts and tools
• Ability to work independently, take ownership, and drive topics forward
• Strong communication skills and the ability to explain technical concepts in clear, simple, and stakeholder-appropriate language
• An outgoing, collaborative personality and a genuine interest in working with colleagues to find good solutions

Nice to have - The following experience would be a strong plus:

• Knowledge of data engineering concepts, such as ETL/ELT pipelines, data transformation, batch processing, data quality, or orchestration tools
• Experience with deployments on hyperscaler platforms such as AWS, Azure, or Google Cloud Platform
• Experience with AI-enabled backend applications, especially RAG-based systems, semantic search, document Q&A, internal knowledge assistants, or agentic workflows using tools such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, OpenAI, Azure OpenAI, Anthropic, or similar technologies
• Familiarity with typical RAG stack components, such as embeddings, chunking, vector databases/search engines like pgvector, Pinecone, Weaviate, Qdrant, OpenSearch, Elasticsearch, or Azure AI Search, as well as observability/evaluation tools such as LangSmith, Langfuse, OpenTelemetry, or Arize Phoenix
• Experience with monitoring, logging, tracing, and observability tools
• Full-stack capabilities and experience in building frontends are a big plus
• Familiarity with security, authentication, authorization, and secure API design
• Experience mentoring engineers or leading technical initiatives