About DSG.AI

DSG.AI combines AI expertise with product thinking and hands-on development to turn business problems into practical applications and workflows.

About the Role

We are looking for a hands-on AI Engineer to own projects end to end, from understanding business needs and researching data to building, deploying, and improving applications.

You will work independently across several projects in parallel, using AI coding tools throughout development. The role requires broad technical understanding and the ability to learn new domains and technologies quickly.

Key Responsibilities

• Work with stakeholders to define requirements and priorities.
• Collect, clean, and combine data from APIs, websites, documents, and datasets.
• Build analytical models, simulations, data pipelines, APIs, and interactive applications.
• Test data, calculations, AI outputs, and application behavior; investigate and resolve issues.
• Explain findings and limitations, incorporate user feedback, and improve deployed tools.

Requirements

• Education and experience: MSc in Computer Science, Information Systems, Data Science, or a related field, plus 2-3 years of Data Science/ML experience; or a bachelor’s degree in one of these fields, plus 4-5 years of relevant experience (Must).
• Strong coding skills (Python or JavaScript) and practical experience working with data (Must).
• Solid foundations in programming, statistics, and machine learning (Must).
• Basic understanding of data systems and system design, including storage, pipelines, and APIs (Must).
• Basic knowledge of cloud infrastructure: compute, storage, networking, and deployment (Must).
• Experience building applications, internal tools, or data products.
• Familiarity with FastAPI, React, Next.js, or TypeScript.
• Experience with LLM APIs, tool calling, structured outputs, and evaluation.
• Background in forecasting, simulation, optimization, or data engineering.
• Familiarity with Docker and automated testing.
• Experience delivering substantial projects with AI coding assistants, including reviewing and debugging generated code and validating outputs.

Soft-skills

• Curiosity and sound analytical judgment: learn unfamiliar subjects, identify data-quality issues, and question unsupported conclusions.
• Self-motivation and a can-do attitude: take initiative, work through ambiguity, and ask for help when needed.
• Good organization and time management, with the ability to prioritize competing tasks and keep multiple projects moving.
• Strong collaboration skills: listen to feedback and communicate progress, blockers, and findings clearly in written and spoken English.

How to Apply

Send your CV and relevant project examples, describing your contribution, use of AI tools, and how you checked the results.

We thank all applicants for their interest; however, we will contact only those selected for an interview.