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Mid-senior Bengaluru role with metro location and mid-level experience but niche ML platform specialization.
Strong ML platform and LLM infrastructure requirements create high domain-specific hiring bias.
Explicit 5+ years requirement plus mandatory ML platform, LLM, Kubernetes, and language experience.
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Own and develop core platform capabilities for a machine learning platform including LLM control plane, model gateways, agent runtimes, and retrieval infrastructure.
Design, implement, and maintain scalable, secure AI infrastructure enabling multi-model LLM integration, AI agents orchestration, and production-grade ML pipelines.
Establish standards for deploying, monitoring, governing, and optimizing both generative AI and traditional ML solutions at enterprise scale.
5+ years experience building large-scale machine learning platforms, data platforms, or distributed software systems.
Strong software engineering skills in distributed systems, concurrency, scalable APIs; proficiency in Python plus Java, Go, or Scala.
Experience with microservices architecture, REST/gRPC APIs, cloud-native design including containers and Kubernetes.
Hands-on experience with MLOps platforms, production ML system deployment, LLM infrastructure, AI agent frameworks, and knowledge graph/vector database technologies.
Experience designing infrastructure as a product with prioritization of developer experience, reliability, observability, and security.
Deep domain expertise in AI platforms integrating classical ML, generative AI, and agent systems with vendor-agnostic architectures.
Proven ability to document complex systems, mentor engineering teams, and optimize for performance, latency, reliability, and cost in enterprise environments.