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Tier-1 employer and Bangalore location increase competition despite niche GenAI specialization.
Specialized GenAI agent and compliance requirements reduce cross-industry transferability to a medium level.
Explicit years plus deep GenAI, ML frameworks, MLOps, and cloud-native requirements create high shortlisting strictness.
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Architect, design, and lead development of production-grade Generative AI and complex Agentic solutions.
Define and drive technical strategy including architecture decisions, agent training, performance measurement, and feedback processes.
Mentor junior/intermediate engineers, oversee Agile project management, and begin formal people management responsibilities (for Manager Track).
7-10 years overall experience; at least 2.5 years in architecting and developing production-ready Gen AI RAG or Agent-based solutions.
Expert-level understanding of Agentic solution design including memory management, hallucination control, and reinforcement learning feedback loops.
Mastery of Python, AI/ML frameworks (PyTorch, TensorFlow, LangChain), MLOps, and cloud-native architectures (Kubernetes).
Bachelor's degree required; Master's preferred in Computer Science, AI, Engineering, or related quantitative field.
Experienced in leading scalable, secure, and high-performance AI technology solutions with strong technical leadership.
Practiced in mentoring technical teams and managing Agile projects with planning and delivering complex AI initiatives.
Capable of transitioning into people management roles with experience in performance reviews and career development.