• LLM Engineering:

Fine-tune and prompt-engineer LLMs for task-specific reasoning, planning, and dynamic adaptation.

Work with LLM/SLM APIs, embeddings, and advanced generative AI techniques.

• Enterprise AI Platform:

Lead the development of enterprise-grade AI platforms integrating LLMs, RAG, embeddings, and agentic AI protocols.

Implement and standardize Model Context Protocol (MCP) for consistent context management across models and agents.

• MLOps & Observability:

Establish and enforce best practices for MLOps, monitoring, and observability, ensuring scalable and maintainable AI solutions.

• Applied AI Prototyping:

Rapidly prototype, experiment, and iterate to improve AI agent capabilities.

• Collaboration & Research:

Participate in the full research cycle: literature review, data exploration, experimentation, and presentation of findings.

Collaborate effectively with other engineers, researchers, and data scientists.

Contribute to the documentation and standardization of technical code and practices.

Required Education

Bachelors degree in Computer Science, Engineering, or a related quantitative field. Master’s or Ph.D. is a strong plus.

Required Experience

• 10years overall experience in software development, data science, or machine learning.
• 3 + year of hands-on experience developing AI applications with LLMs and systems such as retrieval-based methods, fine-tuning, or agent-based architectures.
• 3+ year of experience with frameworks like LangChain, LlamaIndex, OpenAI, or similar tools