Data Scientist

Job Description: Key Responsibilities

• Lead the design and implementation of agentic AI workflows using LangGraph, AutoGen, LangChain, or similar frameworks.
• Architect and optimize scalable APIs (REST/WebSocket) for production deployment.
• Develop, fine-tune, and integrate large language models into enterprise applications.
• Deploy and maintain at least 3 GenAI/Agentic AI projects in production, ensuring reliability, scalability, and performance.
• Integrate SQL, No-SQL, and vector databases such as Postgres, MongoDB, and ChromaDB.
• Implement graph databases (Neo4j) for knowledge graph-based use cases.
• Provide technical leadership and mentorship to engineering teams.
• Collaborate with cross-functional stakeholders to identify and deliver GenAI solutions across multiple business domains.
• Ensure robustness, security, and compliance of deployed AI systems.
• Stay current with trends in GenAI, deep learning, and orchestration frameworks.
• Document and present technical solutions to both technical and non-technical audiences.

Required Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Science, Data Engineering, AI/ML, or related field.
• 7+ years of total professional experience in AI/ML, Data Science, or related fields.
• 5+ years of hands-on experience in Python with strong software engineering practices.
• At least 3 years of experience in AI/ML engineering, including 2+ years of hands-on experience in Generative AI /Agentic AI.
• Hands-on experience with deep learning frameworks (PyTorch, TensorFlow).
• Expertise in large language models (LLMs), prompt engineering, and fine-tuning.
• Proven track record of deploying at least 3 GenAI/Agentic AI projects into production.
• Strong background in Data Science or Data Engineering, including data pipelines, ETL, and data modeling.
• Practical knowledge of SQL, No-SQL, vector databases, and graph databases.

Preferred Qualifications

• Familiarity with LangGraph, AutoGen, LangChain, or similar agentic AI frameworks.
• Experience with multi-agent systems and orchestration of intelligent workflows.
• Knowledge of MLOps practices (CI/CD, model monitoring, retraining pipelines).
• Strong problem-solving skills and ability to thrive in fast-paced R&D environments.
• Contributions to open-source AI/ML projects or published research in generative AI.

Responsibilities: Lead the development and optimization of complex data models, Oversee data science project management and execution, Mentor junior data scientists, Ensure data solutions align with organizational goals, Provide strategic guidance on data science technologies.

Qualifications: Bachelor's/Master's in Engineering 5-8 years