Lead AI Engineer

Architect and develop autonomous AI systems integrating multi-modal LLMs (text, image, audio, video)

Design agentic workflows enabling AI agents to interact with data sources and APIs using prompt engineering and RAG

Fine-tune, optimize, and deploy large language and multi-modal models with a focus on performance and latency

Build scalable MLOps pipelines and full-stack applications to support robust, production-grade AI deployments

Guide multidisciplinary teams and clients through strategic decisions in AI engineering and GenAI adoption

Bachelor’s degree or higher in Computer Science, AI, or related STEM fields

Hands-on experience deploying LLMs and multi-modal models at scale

Strong engineering background in Python with proven backend and API development skills

Solid understanding of scalable MLOps, observability, and cloud-native AI deployment

Excellent communication, problem-solving, and project management skills in agile environments

Experience with agentic frameworks (e.g., LangChain, LlamaIndex)

Experience in deep learning frameworks and front-end development

Familiarity with Langfuse, Langsmith, or other LLM observability tools

Understanding of Model Context Protocol and bias/hallucination mitigation techniques

Previous success in integrating GenAI solutions into enterprise-scale systems