About the role
THE ROLE
Our engineering team thrives on challenging the norm and drawing from diverse technical backgrounds to build some of the industry’s most reliable, intuitive systems. We are forming a dedicated AI Applications team focused on building systems, tools, and processes that elevate the developer experience and accelerate innovation.
We are seeking an experienced Senior Platform Engineer to lead the "Inner Loop" of AI development. In this role, you will bridge high-velocity AI experimentation and enterprise-grade production infrastructure ensuring LLM applications, RAG pipelines, and agentic workflows are built, tested, and deployed with high reliability and efficiency.
WHAT YOU’LL DO
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Deliver Platform Self-Service: Design internal APIs and abstractions allowing engineers to provision AI-ready environments complete with model weights, vector databases, and event streams via single-command automation.
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Build Agentic & Go-Based Automation: Develop robust, type-safe internal tooling and AI agents in Go and Python to automate root-cause analysis, disaster recovery, and proactive infrastructure optimization.
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Scale Event-Driven AI Pipelines: Architect asynchronous processing systems using Kafka and RabbitMQ to trigger dynamic infrastructure scaling and handle high-volume data streams like long-running document ingestion.
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Ensure Reproducible Deployments: Maintain "Golden Path" deployment standards using Docker and Kubernetes to keep models, prompts, and application code perfectly synchronized across all environments.
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Optimize AI Observability & Performance: Manage GPU workloads, distributed caches (Redis), and vector databases while monitoring system health and AI-specific metrics like token latency and model drift.
WHAT YOU BRING
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Relevant Infrastructure Experience: 8+ years of experience in Platform Infrastructure Engineering with an emphasis on supporting AI application development and platform self-service.
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Strong Programming Expertise: High proficiency in Golang.
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Practical AI & Storage Knowledge: Hands-on experience integrating LLM APIs, prompt engineering, and RAG pipelines, alongside expertise in managing vector databases and distributed caches.
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Orchestration & Event-Driven Systems: Deep experience with Kubernetes and asynchronous message streaming via Kafka or RabbitMQ.
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Observability & Reliability Mindset: Strong background in full-stack monitoring Prometheus, Grafana, ELK to maintain operational resilience, high throughput, and zero-downtime standard operating procedures.
We are primarily an in-office environment and therefore, you will be expected to work from the Bangalore office in compliance with Pure’s policies, unless you are on PTO, or work travel, or other approved leave.