AI Engineer

Client of Kalamntina

Responsibilities:

• Design, train, and fine-tune large-scale transformer-based and multimodal AI models for reasoning, dialogue, and contextual understanding.
• Architect and implement multi-agent frameworks enabling AI agents to communicate, plan, and collaborate autonomously on complex tasks.
• Develop structured prompt engineering frameworks and context-management strategies to guide model reasoning, maintain accuracy, and ensure consistent results across agents.
• Design and maintain offline LLM hosting infrastructure, focusing on performance, scalability, and secure model execution through efficient resource utilization.
• Collaborate with data and software teams to define standards for data ingestion, transformation, and preparation to ensure high-quality model inputs and outputs.
• Integrate AI components into existing systems using standardized communication, orchestration, and context-exchange protocols for interoperability.
• Establish monitoring, benchmarking, and validation processes to track model accuracy, efficiency, and reliability in production environments.
• Explore advancements in agentic AI, autonomous reasoning, and generative model infrastructure, applying innovations to strengthen platform scalability and intelligence.

Qualifications:

• Bachelor s degree in computer science, AI, or a related field, with a minimum of 3 years in AI or machine-learning engineering roles.
• Proven experience with LLMs, Generative AI, or multi-agent system development, including offline or distributed inference environments.
• Strong understanding of transformer architectures, context handling, multi-agent coordination, and prompt engineering.
• Proficiency in AI model lifecycle management, data preparation, evaluation frameworks, and system integration.
• Analytical thinker with excellent problem-solving skills, adaptable to emerging technologies in Generative and Agentic AI.
• Collaborative, with strong communication skills, and focused on performance, scalability, ethical deployment, and long-term sustainability of AI solutions.