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Tier-1 brand and Bangalore location increase applicant density, balanced by senior niche GenAI specialization.
Specialized GenAI architecture, LLMs, RAG, and enterprise compliance requirements make cross-industry transferability low.
Explicit 10–15 year requirement plus mandatory GenAI architecture, MLOps, and governance skills imply high filtering.
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Own end-to-end architecture and technical design of production-ready AI and Generative AI solutions, including LLM applications, RAG systems, and agentic workflows.
Design and implement production readiness including LLMOps/MLOps, evaluation frameworks, monitoring, observability, cost-efficient inference, and compliance with Responsible AI and security standards.
Serve as senior technical authority guiding delivery teams, resolving escalations, and supporting client technical engagements and workshops.
10–15 years experience in software/ML engineering and architecture with proven ownership of AI solutions in production.
Strong hands-on expertise in GenAI architecture: LLMs, RAG, agentic patterns, orchestration frameworks and tools such as Langchain, Haystack, Llama Index.
Practical experience with MLOps/LLMOps, evaluation design, model serving, observability, inference cost optimization, and Responsible AI/security/compliance design.
Bachelor's degree in Engineering (B.E/B.Tech), MCA, PhD, or equivalent.
Demonstrated ability to architect complex AI solutions balancing technical trade-offs such as build vs buy, model selection, and retrieval design at scale.
Experience liaising with cross-disciplinary teams including Data Solution Architects to align AI and data foundation strategies.
Comfortable leading technical workshops and communicating complex AI concepts and trade-offs to diverse technical stakeholders in client environments.