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Senior, niche LLM/MLOps role in Bangalore reduces broad applicant competition but attracts specialized AI platform candidates.
Strong specialized AI platform and MLOps focus makes it moderately transferable, benefiting candidates from ML/AI infrastructure backgrounds.
Explicit 8+ years plus mandatory MLOps/LLM, cloud, and platform skills enforce strict technical shortlisting.
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Own and operate the LLM control plane and gateway enabling safe, cost-efficient, multi-provider LLM usage with SLAs and quality/cost guardrails.
Build and manage agent runtime including orchestration patterns, permission controls, and long-running workflow management to drive AI-powered dealer outcomes.
Develop and maintain platform components for classical ML models, monitoring model/data drift, and enabling real-time context and retrieval for agents.
8+ years experience in large-scale data/ML or platform system engineering.
Strong software engineering skills with production experience in Python and one of Java/Scala/Go, including microservices and API design.
Hands-on experience building or operating an LLM gateway/control plane with provider adapters, routing policies, caching, and cost accounting.
Familiarity with cloud (AWS preferred), containerization (Docker/Kubernetes), MLOps pipelines, and graph/vector retrieval technologies.
Experience working on end-to-end AI-native platforms integrating LLMs and classical ML models for business-critical applications.
Expertise in building scalable, resilient multi-tenant SaaS platforms with strong emphasis on observability, access control, and cost optimization.
Skillset in systems design focusing on developer experience, platform-as-product mindset, and implementing safety/guardrails for agentic AI systems.