Hybrid Associate AI Engineer at Kaleris

Key Responsibilities

• Support the development of GenAI agents and AI-based workflows under the supervision of senior engineers.
• Assist in creating, optimizing, and evaluating prompts for Large Language Models (LLMs) and other generative systems.
• Collaborate on integrating vector databases and retrieval-augmented generation (RAG) techniques to improve knowledge retrieval in AI applications.
• Contribute to the documentation, testing, and deployment of GenAI solutions.
• Participate in cross-team meetings and brainstorming sessions, sharing ideas and learning from experienced colleagues.
• Help develop internal tools and automation tasks to streamline processes.
• Stay current with emerging technologies by reading documentation, attending training, and participating in internal seminars.

Qualifications

Required:

• Bachelor’s degree (or in final year) in Computer Science, Engineering, Data Science, or related field; relevant internship or project experience considered.
• Programming proficiency in Python required; familiarity with JavaScript, Java, or C is a plus.
• Foundational knowledge of GenAI principles (LLMs, RAG, agent workflows—via coursework, internships, or personal projects).
• Familiarity with cloud services (AWS preferred) and version control (Git).
• Effective verbal and written communication skills and willingness to learn.

Preferred:

• Hands-on experience with a cloud platform (AWS, Azure, or GCP).
• Practical exposure to frameworks like LangChain or vector databases and basics of front-end/back-end development.
• Participation in research, hackathons, or open-source GenAI/ML projects.
• AWS, cloud, or AI certifications are a plus.

Soft Skills

• Curiosity, willingness to ask questions, and openness to feedback.
• Team-oriented mindset and ability to work in a collaborative environment.
• Reliable, detail-oriented, and proactive about learning and contributing.