Data Scientist (Gen AI)

ScryAI; Bengaluru; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

ScryAI is seeking a highly skilled Senior Data Scientist to lead the development and deployment of advanced Generative AI solutions. The ideal candidate will have over 4 years of experience in data science, a strong background in Python and modern LLMs like OpenAI, as well as expertise in Retrieval-Augmented Generation techniques.

This role involves architecting scalable AI applications, designing data pipelines, and mentoring junior team members. Candidates should demonstrate hands-on experience in taking prototypes to production and have a strong analytical mindset.

Qualifications

• 4+ years of experience in GenAI, data science, or AI-focused roles.
• Advanced proficiency in Python and extensive experience with modern LLMs.
• Strong background in RAG methods and architectures.

Responsibilities

• Architect and deploy scalable GenAI applications using OpenAI.
• Design and orchestrate data pipelines leveraging Kedro.
• Integrate LangChain to develop advanced natural language workflows.

Skills

Python

OpenAI APIs

Kedro

Docker

LangChain

Retrieval-Augmented Generation

Education

Bachelor’s or master’s degree in computer science or related field

Tools

Postgres

MongoDB

Job description

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.