Senior AI Engineer

Overview of the position

The Senior AI Engineer collaborates with other expert talents to develop, maintain, and assist in the deployment of natural language processing (NLP) AI products, from RAG systems to content generation and recommendation, to improve Enhesa’s customer experience. In addition to the required technical skills, the Senior AI Engineer has great organizational and communication skills and understands the challenges related to working with different languages.

The Senior AI Engineer is expected to keep up with the latest developments in the field of Artificial Intelligence engineering and be prepared to think creatively and apply novel techniques while solving business problems.

Main tasks and responsibilities

• Being comfortable with experimentation and showing a willingness to approach a problem in multiple ways via rapid prototyping.
• Identifying appropriate datasets and driving annotation for machine learning techniques.
• Developing and maintaining machine learning applications and products, together with relevant expert talents.
• Iteratively improving the developed AI systems and running evaluation experiments in collaboration with others, performing statistical analysis of results.
• Keeping an eye on the state-of-the-art of machine learning and GenAI solutions, emerging technologies, and developments in academia.
• Translating and communicating technical concepts and solutions to different stakeholders.

Key requirements

Education Level

Bachelor’s or advanced degree in Computer Science, AI, Mathematics, or a related field.

Experience

At least 3 years of experience as an AI/IT Engineer (More than 5 years if the highest education is a Bachelor’s degree). 

Technical Skills:

• Postgres database or other relational database experience.
• Familiarity with the concepts and applications of Vectors Database knowledge is a plus.
• Experience in content apps and microservices.
• Knowledge of a variety of NLP techniques, RAG Systems, Agentic Orchestration, MCP servers, classification, data transformations, optimization, and deep neural networks, with a good understanding of the mathematical underpinnings and real-world advantages/drawbacks preferred.
• Knowledge of data structures, semantic extraction, and text representation in an NLP context.
• Proficiency in Python (OOP) preferred.
• Experience in using technologies such as Docker, Azure, GCP, and AWS.
• Experience in creating application programming interfaces (APIs), such as RESTful, Asynchronous, etc.
• Ability to write clean, production-ready code.

Other Skills:

• Any other core skills to bring to the team are a huge plus, such as front-end development, experience administering cloud systems, deploying serverless cloud technology, deep Linux knowledge, etc.
• Fluency in English. Any additional language skills are an asset.
• In order to fit in Enhesa’s collaborative and international environment, creativity, dynamics, and ability to work independently yet transparently towards colleagues.
• Strong teamwork skills, both with colleagues as well as with external partners.
• Both individual and team problem-solving skills are crucial in this position.