About Enterpret

Enterpret is at the forefront of AI-native applications, unlocking the power of customer feedback for businesses. We centralize feedback from every channel and transform it into actionable insights that drive customer-centric decisions for teams at the world's leading companies like Perplexity, Notion, Canva, and Figma. Backed by investors such as Kleiner Perkins and Peak XV, we're redefining how businesses understand and act on the voice of their customers.

About the Role

As LLMOps Architect at Enterpret, you'll be responsible for how LLM models are fine-tuned, how prompts are managed, how we run evals, how we optimize for cost, and how we optimize for speed—both at the experimentation stage and in production. This is a foundational, high-ownership role where you'll work directly with the OpenAI and Anthropic teams (whom we partner with closely), as well as AWS (whom we partner with closely), to build world-class ML infrastructure.

You'll work closely with ML researchers, backend engineers, and product teams to ensure our AI systems are resilient, secure,



and cost-productive as we grow 10x. Key success metrics include improving the speed of experimentation, time to productionization, and the quality of models. You'll report directly to the CTO.

What You'll Do

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Design and evolve Enterpret's ML platform for training, serving, and retraining our encoders and LLM models using AWS/Terraform/OpenAI/Anthropic.

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Build CI/CD pipelines tailored for ML—including model versioning, testing, canary releases, rollbacks, and gated production deploys.

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Deploy and manage model serving systems for both real-time inference (e.g., tagging support tickets on the fly) and batch pipelines (e.g., analyzing historical product feedback).

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Set up observability for model performance and data drift—using Braintrust and custom alerts to catch issues before they affect customers.

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Lead incident response, root cause analysis, and postmortems for ML systems—ensuring up

📌 LLMOps Architect (Bengaluru)
🏢 Enterpret
📍 Bengaluru