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Tier-1 brand and Bengaluru metro increase competition, while specialized GenAI skills moderate applicant density.
Requires specialized GenAI, LLMOps, and platform engineering skills, limiting cross-industry transferability.
Explicit 7+ years plus many mandatory GenAI, LLMOps, and platform engineering requirements increase filter strictness.
Advise leadership on developing or influencing enterprise applications and technologies for complex business needs across multiple groups.
Lead strategy and resolution of highly complex technical challenges delivering long-term, large-scale solutions requiring innovation and advanced analytical thinking.
Provide vision and technical expertise on implementing innovative business solutions while maintaining knowledge of industry best practices and new technologies.
7+ years of engineering experience (including work experience, training, military experience, or education).
Not explicitly mentioned in the JD: specific degree requirements.
Not explicitly mentioned in the JD: location or onsite requirements.
Not explicitly mentioned in the JD: notice period.
Proven experience designing and scaling enterprise GenAI platforms and AI-driven products with expertise in Agentic AI, multi-agent systems, RAG architectures, Knowledge Graphs, and long-term memory frameworks.
Strong cloud-native engineering background with Kubernetes, microservices, containers, distributed systems, and hands-on experience with cloud AI platforms such as Azure OpenAI, AWS Bedrock, and Google Vertex AI.
Experience with model orchestration solutions, LLMOps, AI security, responsible AI, governance, and solid understanding of AI platform engineering including CI/CD automation and production-grade AI deployments.