AI Software Engineer

Who we are

At Software Improvement Group (SIG), we assist organizations in enhancing software quality through in-depth source code analysis and strategic advice. Our software portfolio governance platform, Sigrid, combined with the expertise of our consultants, empowers customers to take control of their software environments, making technology a driver of success rather than a source of risk.

Within SIG, the AI R&D team in the CTO Office is dedicated to innovation in AI for software engineering. Instead of integrating features directly into our core product from the start, we develop experimental prototypes that can be tested quickly with clients and internal teams. Successful prototypes are then further developed into comprehensive solutions.

We are seeking an AI R&D Engineer to help us explore and prototype innovative AI-driven solutions for software engineering. This role lies at the intersection of experimentation, engineering, and applied research.

In this position, you will focus on developing rapid prototypes, AI-powered applications, and conducting internal experiments using tools such as large language models (LLMs), prompt engineering, and AI coding assistants. Additionally, you will contribute to data analysis and machine learning efforts, particularly in the areas of software quality and development processes.

This role is ideal for someone who enjoys quickly building and testing ideas in a fast-paced environment where not everything is defined upfront.

You will join a small, innovation-focused team that provides ample opportunity to experiment and shape direction. Your work will significantly impact SIG’s AI strategy, client‑facing innovations, and future product ideas.

• The chance to work on cutting‑edge AI applications in software engineering.
• Freedom to experiment, prototype, and learn quickly.
• Close collaboration with colleagues in research, consulting, and software development.
• A flexible, remote‑first setup, with the team meeting in the office approximately once per week.
• An opportunity to help define how AI is applied across SIG.

As an AI R&D Engineer, you will focus on practical AI innovations within the software engineering field. Your primary responsibilities will involve rapid prototyping and experimentation, as well as contributing to applied machine learning (ML) and data‑driven analysis when applicable.

Examples of tasks you may undertake include:

• Building experimental AI‑powered applications and proof‑of‑concept projects.
• Prototyping with large language models (LLMs), prompt engineering, and AI coding assistants, including tools such as Claude and Git Hub Copilot.
• Exploring AI‑assisted workflows, automation, and agent‑based approaches for software engineering.
• Collaborating with customers, developers, consultants,and researchers to identify and develop new AI use cases; applying data analysis, machine learning or statistical techniques as relevant; and helping to transform promising prototypes into practical next steps.

You are curious, hands‑on, and motivated to build and test new ideas. You enjoy using AI tools in practice rather than just discussing them theoretically. You are comfortable learning as you go, working with imperfect information, and iterating quickly. You likely have a background in software development, AI, or applied research and development, and you are excited about the opportunity to help shape the use of AI in a software‑engineering company.

• A master’s degree or PhD (preferred) in Computer Science, Software Engineering, Artificial Intelligence, or a related field.
• 2 to 4 years of relevant experience in AI, software engineering, applied research, or prototyping.
• Proficiency in both Java and Python, along with a solid foundation in general software development skills.
• Practical experience with large language models (LLMs), such as in prototyping, prompt engineering, or application development.
• An interest in or experience with AI coding assistants, coding agents, and rapid experimentation.
• Some background in machine learning, data analysis, or related experimentation, coupled with an affinity for software engineering and developer workflows.
• Strong communication skills, a proactive and self‑directed mindset, and the ability to work comfortably in ambiguous situations; excellent command of the English language.

• Proficient in machine learning frameworks and tools, including PyTorch, Tensor Flow, scikit‑learn, XGBoost, and Light
  
  GBM.
• Experienced with AWS, Docker, and containerised development workflows.
• Familiar with AWS Bedrock, Ollama, local deployment of large language models (LLMs), and automation patterns involving AI agents.
• Background in software engineering research, including implementing concepts from academic papers and rapidly prototyping simple user interfaces using AI tools.