AI Engineer

Are you a versatile AI Engineer who uses technology as a means to solve real business problems? Do you enjoy challenging assumptions, uncovering the true needs behind a client’s request, and developing tailored AI solutions that make a lasting impact? Do you want to strengthen and expand your technical skills under guidance of experienced AI engineers?

At Datashift, we’re looking for an AI Engineer who excels in crafting challenging technical solutions that deliver business value. You’ll work closely with clients to reveal the core challenges before diving into solutions, selecting the best-fit approach—whether it’s generative AI, machine learning, statistical modeling, or something entirely different. You’ll build scalable applications from proof-of-concept to production, always keeping security and privacy top of mind.

Responsibilities

• We see AI as a means, not as a goal. We’re looking for an AI Engineer who always searches for the best technology to address specific data related business problems, whether it’s genAI, machine learning, statistical models, or other methods

• Build AI solutions from proof of concept to fully integrated applications, together with other Datashift experts

• Translate fuzzy client requirements into creative, pragmatic solutions, delivering rapid proof of concepts to quickly validate ideas and show business value

• Scale and harden proven prototypes into robust, production-grade, and secure AI applications

• Ensure customer constraints such as security and privacy are met as from the start when developing solutions

• Communicate effectively about your technical solution towards different stakeholders at all levels

• Work in an agile way and adapt to changing business needs

Qualifications

• At least 2 years of experience in industry, including experience in consultancy (preferred)

• Background in business engineering, civil engineering, or related field

• Strong Python & SQL skills, with a focus on data cleaning, preprocessing, and building robust pipelines

• Knowledge of AI, combining traditional machine learning with modern GenAI solutions (e.g., RAG, agentic workflows)

• First experience with cloud platforms (AWS, Azure, or GCP) to deploy and manage AI solutions.

• Affinity with software engineering best practices (clean, modular code, pytest, Git) and DevOps tooling (Docker, CI/CD)

• Experience with successful delivery of an AI project in production environment

• Excellent communication skills, and proven success in contributing to a team-oriented environment