Senior AI Software Engineer

We are looking for an experienced Senior AI Software Engineer to join our team and contribute to the development of Artificial Intelligence solutions supporting our engineering and R&D activities.

The position combines software engineering and Generative AI. You will design and develop applications leveraging Large Language Models (LLMs), enterprise data and modern AI platforms, while ensuring that these solutions can be effectively integrated into our existing software environment.

You will work closely with software engineers, architects, technical experts and project stakeholders to identify relevant AI use cases and transform them into practical, reliable and maintainable solutions.

As an experienced member of the team, you will be expected to work with a high degree of autonomy, contribute to technical and architectural decisions, and share your knowledge with other engineers working on AI initiatives.

Design and Develop AI Solutions

• Design and develop applications and services leveraging Large Language Models (LLMs) and Generative AI.
• Build AI-powered solutions supporting engineering and R&D activities.
• Develop solutions using Microsoft Azure AI services and Azure AI Foundry, as well as other approved AI technologies when appropriate.
• Design and implement Retrieval-Augmented Generation (RAG) solutions combining LLMs with internal documents, knowledge bases and enterprise data.
• Integrate AI models through APIs and SDKs into new or existing applications.
• Design AI workflows involving multiple processing steps, models, tools or data sources.

• Explore multimodal use cases involving text, documents and images when relevant.

Develop Enterprise Software

• Design and develop backend applications, services and REST APIs.
• Contribute to applications primarily based on C# and .NET / ASP.NET Core within the existing enterprise software environment.
• Use Python when appropriate for AI development, experimentation, data processing or integration with the broader AI ecosystem.
• Integrate applications with databases, enterprise systems and external APIs.
• Write maintainable, reliable and well-documented code.
• Diagnose and resolve technical issues across AI and application components.

• Contribute to the technical architecture of new AI solutions.

Evaluate and Improve AI Solutions

• Evaluate different AI models and approaches according to the requirements of each use case.
• Design and improve prompts, system instructions and context-management strategies.
• Understand and manage concepts such as tokens, context windows, embeddings and vector search.
• Evaluate AI outputs in terms of quality, reliability and consistency.
• Consider performance, latency and cost when designing AI solutions.
• Identify limitations and risks associated with LLM-based solutions and propose appropriate technical approaches.

• Contribute to the continuous improvement of existing AI applications based on usage and feedback.

Explore and Recommend Technologies

• Follow developments in Generative AI, LLMs and related technologies.
• Experiment with new models, frameworks and approaches when they could bring value to the organization.
• Compare technical alternatives and contribute to technology and architecture choices.

• Help determine when Generative AI is appropriate for a use case and when a traditional software approach may be more suitable.

Collaborate and Share Knowledge

• Work with engineers and domain experts to understand their needs and identify valuable AI use cases.
• Translate functional needs into appropriate technical solutions.
• Explain technical concepts and architectural choices to both technical and non-technical stakeholders.
• Produce and maintain technical documentation for developed solutions.
• Share knowledge and good practices with other developers.
• Provide technical guidance to junior engineers or students contributing to AI projects.

Required Skills & Qualifications

• Bachelor's or Master's degree in Computer Science, Software Engineering, Artificial Intelligence or a related technical field, or equivalent professional experience.
• Significant professional experience in software development.
• Strong backend development and software engineering skills.
• Professional experience with C#/.NET and/or Python, with the ability and willingness to work with both technologies when required.
• Hands-on experience developing applications or services using Generative AI and Large Language Models.
• Good understanding of LLM concepts such as prompting, context management, tokens and model limitations.
• Experience integrating services and systems through REST APIs.
• Experience working with relational databases and data-driven applications.
• Good understanding of software architecture and application integration.
• Ability to investigate complex technical problems and propose pragmatic solutions.
• Ability to work autonomously and take ownership of technical topics.
• Good communication and collaboration skills in an international environment.
• Professional working proficiency in English.

Nice to have

The following skills are valuable but are not mandatory:

• Experience with Microsoft Azure AI Foundry or similar enterprise AI platforms.
• Experience with Retrieval-Augmented Generation (RAG) architectures.
• Knowledge of embeddings, vector databases and semantic search.
• Experience with AI orchestration frameworks such as Microsoft Semantic Kernel or equivalent technologies.
• Experience working with both C#/.NET and Python in professional projects.
• Experience with ASP.NET Core and enterprise web applications.
• Experience integrating AI solutions with enterprise data sources or business systems.
• Experience with AI evaluation, observability or usage and cost monitoring.
• Knowledge of locally deployed or open-source LLMs.
• Experience with multimodal AI, document processing, Vision models or OCR.

• Experience using AI-assisted development tools.

What we are looking for

We are looking for an experienced engineer who combines strong software development skills with practical Generative AI experience.

The ideal candidate should be able not only to experiment with an LLM, but also to transform an AI concept into a maintainable application that can interact with existing systems and enterprise data.

We value technical curiosity and pragmatism. The AI ecosystem evolves quickly, so the ability to evaluate new technologies, understand their strengths and limitations, and select the right approach for a given problem is more important than expertise in any single framework.

We are also looking for someone who can bring experience to the team: an engineer capable of working independently, contributing to technical decisions and helping less experienced team members develop their AI engineering skills.