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Tier-1 brand and metro location increase competition, but senior GenAI specialization narrows applicant pool.
Highly specialized GenAI, agentic architecture, and RL requirements limit cross-industry transferability.
Explicit 7-10 years, mandatory GenAI architecture experience and specific tech stack create strict filtering.
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Architect, design, and lead production-grade Generative AI and complex Agentic solution development ensuring compliance, security, and performance standards.
Define and drive technical strategy for AI projects, making key architecture and tool decisions, including agent training and feedback process designs.
Mentor junior/intermediate engineers and data scientists; oversee Agile project management and begin formal people management responsibilities if on manager track.
7-10 years total experience, with at least 2.5 years in architecting and developing production-ready Generative AI RAG or Agent-based solutions.
Expert-level knowledge in Agentic solution design including memory management, hallucination control, and reinforcement learning feedback loops.
Proficient in 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, high-performance AI technology solutions from architecture through deployment in production environments.
Strong technical leadership skills with proven ability mentoring engineering and data science teams in complex AI projects.
Comfortable managing multiple deliverables in Agile settings with knowledge of project/program management and compliance/security in AI solutions.