Senior Artificial Intelligence Engineer - RAG/LLM Models (6-8 yrs)

Experience : Min 6-8 years.

Essential Qualifications :

- Advanced degree (Master's or higher) in Computer Science, Engineering, or a closely related technical discipline.

- Proficiency with Retrieval-Augmented Generation (RAG) techniques and experience working with vector databases (e.g , Weaviate, PineCone).

- Extensive Python programming skills, with a proven ability to implement complex solutions.

- At least 1 year of practical experience in building applications based on Large Language Models (LLMs) using established third-party models (e.g , OpenAI, Anthropic).

- Skilled in prompt engineering, with experience crafting function calls and constructing conversational AI applications.

- Familiarity with advanced LLM techniques such as zero-shot and few-shot learning, as well as fine-tuning for specific use cases.

- Strong background in using Generative AI libraries and tools, such as Langchain and HuggingFace.

- Solid grasp of version control practices, including Git and collaborative development workflows.

- Comprehensive experience in preparing, managing, and processing extensive datasets, both structured and unstructured.

- Proven experience deploying, scaling, and monitoring machine learning models, particularly LLMs, in live environments.

- Flexible to accommodate occasional overlap with US Eastern Time for effective team collaboration.

- Professional proficiency in English.

Desirable Additional Experience :

- Hands-on experience with open-source LLM frameworks, such as Llama or Mistral.

- Prior work involving data in regulated sectors, such as healthcare, banking.

Technical Skills and Capabilities :

- Skilled in RESTful API design (Python-FastAPI) and development, ensuring secure and scalable interfaces.

- Proficient in JavaScript for both front-end and back-end, with a strong command of associated frameworks.

- Knowledgeable in architecting scalable solutions using microservices.

- Experience with the generative AI landscape, specifically around RAG, vector embeddings, LLMs, and open-source AI toolkits.

- Familiarity with cloud-based infrastructure (AWS, Azure, GCP) and their data services.

- Competent in database design and optimization across SQL and NoSQL technologies.

- Agile development experience, using tools like Git, Jenkins, and Azure DevOps.

- Excellent team collaboration and communication skills, with an aptitude for working across technical and non-technical roles.