GenAI Architect

About the Role

We are seeking a skilled GenAI Architect to lead the design, implementation, and co-development of cutting-edge generative AI solutions. The ideal candidate will be both a practitioner and an architect, capable of evaluating and guiding multiple AI solutions while working closely with client teams.

Key Responsibilities

· Design and develop scalable, enterprise-grade AI solutions using LLMs and other ML models, with a focus on healthcare challenges

· Ensure AI systems prioritize privacy, security, fairness, and adhere to responsible AI practices

· Architect and implement AI outputs in various formats (JSON, arrays, HTML) for seamless integration into dashboards

· Build extensible API integrations and low-code UI/UX solutions with short development cycles

· Develop and optimize AI pipelines, including data preprocessing, feature extraction, model training, and evaluation

· Work with frameworks (TensorFlow, PyTorch) and open-source platforms like Hugging Face

· Collaborate with Product Development as a Generative AI subject matter expert

· Create clear documentation and communicate complex AI concepts to diverse stakeholders

· Establish best practices and standards for generative AI development within the organization

Required Qualifications

· Bachelors in Computer Science, AI, or related field

· 5+ years of full-stack engineering expertise with languages like C#, Python, and proficiency in designing architecture

· Experience in implementing enterprise AI systems in production settings, including computer vision and NLP

· Strong understanding of natural language generation, Gen AI, transformers, LLMs, and text embeddings

· 3+ years of experience in a technical leadership role, leading project teams and setting technical direction

· Expertise in machine learning libraries and frameworks (PyTorch, TensorFlow, Hugging Face, LangChain, Llama Index)

· Experience with cloud platforms (AWS, GCP, or Azure) and containerization technologies

· Strong problem-solving skills and ability to think critically and creatively

Preferred Qualifications

· Experience with self-supervised learning, transfer learning, and reinforcement learning

· Familiarity with vector databases like Pinecone

· Knowledge of AI ethics and responsible AI practices