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Senior Data Science Lead (Gen AI/ Agentic AI) - Vice President
On-site · Bengaluru, Karnataka, India
Job Summary
Lead the architecture, design, and development of mission-critical, production-grade Generative AI applications and Agentic solutions. Define and own the technical roadmap for AI platforms, drive agent-centric design including memory management, hallucination control, and reinforcement learning-based feedback loops. For VP track, lead and mentor a team of engineers and data scientists, drive compliance, security, MLOps, and Model Governance, and communicate with senior stakeholders. Strong emphasis on strategic thinking, Innovation, and staying ahead of AI research trends. Candidates should have deep expertise in Generative AI, RAG/Agentic architectures, Python, PySpark, SQL, Hive, data preprocessing/visualization, hypothesis testing, predictive modeling, and performance optimization, along with leadership experience and excellent stakeholder management.
Required Qualifications
- 10-15 years of overall experience
- minimum of 3 years leading the development of production-ready Gen AI RAG or Agent-based solutions
- extensive experience as a full-stack development manager or architect
- deep expertise in architecting and designing complex Agentic solutions
- mastery of agent training, performance measurement, and feedback processes
- strong people management skills with experience in grooming and developing engineers
- experience in program/project management, Agile processes
- knowledge of financial services compliance, security, and performance management
- proficiency in Python, modern AI/ML frameworks, and cloud-native technologies
- education: Bachelor's degree; Master's degree highly preferred in Computer Science, AI, Engineering, or related quantitative field
- experience with Langchain frameworks, Langgraph, Google ADK, RAG, and Big Data technologies
- proficiency in scripting languages (Python)
- hands-on experience with data analysis, statistical methods
- communication skills for translating technical concepts to non-expert audiences
- experience with MLOps and Model Governance
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