Gen AI Architect

Role & Responsibility

• Advanced degree (Master s or higher) in Computer Science, Engineering, or a closely related technical discipline.
• Minimum of 3 years of hands-on experience with a range of machine learning models, spanning traditional to advanced methods.
• Solid foundation in NLP methods, including applications like text classification, sentiment detection, and entity recognition.
• 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.
• Practical experience with data streaming platforms, such as Kafka, Azure Event Hub, or AWS Kinesis.
• Agile development experience, using tools like Git, Jenkins, and Azure DevOps.
• Skilled in creating and managing CI/CD pipelines for seamless testing and deployment.
• Excellent team collaboration and communication skills, with an aptitude for working across technical and non-technical roles.

Must Skills

• Gen AI
• AWS
• SQL