Description

• Working with client stakeholders to gather requirements and translate them into AI/GenAI-based solutions.
• Designing, developing, and deploying Generative AI models leveraging LLMs (OpenAI, Anthropic, Hugging Face, etc.).
• Building prompt frameworks, embeddings, and retrieval-augmented generation (RAG) pipelines.
• Integrating AI models with enterprise workflows, APIs, and client applications.
• Fine-tuning/customizing foundation models for client-specific use cases.
• Ensuring model performance, scalability, and cost efficiency.
• Documenting solution designs, architecture, and providing knowledge transfer to client/internal teams.
• Applying strong programming skills in Python and working with GenAI frameworks and vector databases (Pinecone, Weaviate, FAISS).
• Utilizing cloud platforms (AWS, Azure, GCP) for AI/ML deployment along with Git/GitHub and CI/CD workflows.
• Collaborating with business and functional teams through strong problem-solving and communication skills.
• Bringing in added expertise with ML Ops practices, data engineering tools (Airflow, DBT, Spark), and Life Sciences/Healthcare applications (preferred)

Key Skills

Education

Bachelor's degree