AI Platform Architect

2 weeks ago

varanasi, India beBeePlatform Full time

We are seeking a highly skilled AI platform engineer to design, build and operate our next-generation AI application platform.This role will focus on advanced AI systems including Retrieval-Augmented Generation (RAG) pipelines, multi-model gateways and Model Context Protocol (MCP) tools.You will be responsible for ensuring the production readiness of all platform components, covering Infrastructure as Code (IaC), CI/CD pipelines, Kubernetes orchestration, observability, cost optimization and governance.The ideal candidate will have strong hands-on programming experience in Python, Go or TypeScript and expertise with Kubernetes, container orchestration and cloud-native tooling.The following are some key responsibilities:Design, develop and operate the company's AI application platform, including RAG pipelines, model gateways and MCP integrations.Build and maintain secure chat interfaces using OpenWebUI or custom UI components.Own IaC (Terraform, Helm, etc.), CI/CD automation and Kubernetes-based deployments for all AI platform components.Implement robust observability solutions (monitoring, logging, tracing) across the platform.Ensure platform reliability, uptime and scalability using SRE and DevOps best practices.Optimize compute, storage and inference costs while maintaining performance and quality.Establish strong governance, access control and compliance processes across AI workloads.Required skills and qualifications include 4–10+ years of experience in software engineering, DevOps or AI/ML platform engineering, strong hands-on programming experience in Python, Go or TypeScript and expertise with Kubernetes, container orchestration and cloud-native tooling.Experience building RAG pipelines, LLM integrations or similar AI workflows is also desirable.The following are some preferred qualifications:Experience with multi-model routing, inference gateways or vector databases.Knowledge of MCP (Model Context Protocol) and related developer tooling.Prior experience scaling AI or distributed systems in cloud environments (AWS, GCP, Azure).Understanding of SRE principles, access governance and security best practices.Become part of a team that delivers scalable, secure and high-performing AI-driven applications.

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