About the Role:
We are seeking a highly skilled and innovative Senior Data Scientist to join our dynamic team and lead the development and deployment of advanced Generative AI (GenAI) solutions. The ideal candidate will have significant hands-on experience with large language models (LLMs) such as OpenAI and Claude, Retrieval-Augmented Generation (RAG) architectures, and frameworks like LangChain. Experience with Kedro for data pipeline orchestration and Docker for deployment is required. The candidate must have a
proven track record of taking GenAI prototypes to production in real-world environments.
Key Responsibilities
Architect, build, and deploy scalable GenAI applications using OpenAI, and Retrieval-Augmented Generation (RAG) techniques.
Design and orchestrate modular, reproducible, and robust data pipelines leveraging Kedro for end-to-end machine learning workflows.
Integrate LangChain to develop advanced natural language workflows and enhance AI-powered applications.
Take GenAI prototypes from concept to production, ensuring reliability, scalability, and maintainability in real-world environments.
Containerize machine learning and GenAI solutions with Docker for seamless deployment and scalability across cloud and on-premises platforms.
Collaborate with cross-functional teams—including Engineering, Product, and Operations—to align AI solutions with business goals and deliver measurable impact.
Mentor and support junior team members, sharing best practices in data science, MLOps, and GenAI deployment.
Continuously evaluate and implement emerging AI technologies, driving innovation and excellence in our AI capabilities.
Key Qualifications
4+ years of experience in GenAI, data science, machine learning, or AI-focused roles. 2+ years of experience in GenAI.
Advanced proficiency in Python; extensive experience with OpenAI APIs, and other modern LLMs.
Strong background in Retrieval-Augmented Generation (RAG) methods and architectures.
Proven expertise with LangChain for natural language processing and workflow automation.
Demonstrated experience taking GenAI prototypes to production environments.
Experience building and orchestrating data pipelines with Kedro.
Proficient in Docker-based containerization and deployment (Kubernetes a plus).
Knowledge of data engineering and software engineering best practices.
Excellent communication, collaboration, and mentoring skills.
Bachelor’s or master’s degree in computer science, Data Science, Engineering, or a related field.
Experience with working on SQL DB like Postgres and No-SQL DB like MongoDB
Preferred Qualifications
Experience with AWS or other major cloud platforms.
Experience with CI/CD tools and automated testing frameworks.
Open-source contributions, technical presentations, or publications in AI/ML.
Previous leadership or mentorship of technical teams.
Building Backend Python APIs
