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Senior, niche LLMOps platform role in Bangalore with moderate brand attracts targeted applicants.
Core LLMOps and AI platform skills transfer across industries, but industrial automation domain adds specificity.
Multiple mandatory seniority and specialized LLMOps, Azure, and architecture requirements enforce strict filtering.
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Define and govern architecture standards, roadmaps, and engineering practices for ABB's Enterprise AI Platforms including Copilot ecosystems and Agentic AI frameworks.
Lead design and governance of scalable, secure, cloud-native AI platforms covering LLMOps, MCP, RAG, integrations, observability, and cybersecurity.
Provide technical leadership and mentorship across engineering teams and collaborate with cross-functional stakeholders for delivery of strategic AI platform initiatives.
Bachelor's or Master's degree in Computer Science, Software Engineering, AI, Data Science, or related technical field.
10+ years of experience in enterprise software engineering, solution architecture, and technical leadership for large-scale cloud-native distributed systems.
Expertise in Generative AI, LLMs, LLMOps, Agentic AI, MCP, RAG, AI governance, vector databases, and enterprise AI platform architecture.
Hands-on experience with Microsoft Azure services (Azure OpenAI Service, AKS, App Services, Azure SQL, Cosmos DB), Kubernetes, Docker, IaC, cloud security, and DevSecOps practices.
Experienced senior technical leader capable of defining and governing enterprise AI platform architecture and engineering standards in complex cloud-native environments.
Strong background in AI platform engineering with significant hands-on and leadership experience in Generative AI technologies, LLMOps, and secure AI systems.
Ability to collaborate effectively across product management, AI/ML, DevOps, and security teams in Agile global organizations, and mentor technical teams.