AI Platform Engineer

6 days ago

Delhi, India BayOne Solutions Full time

Job Description We are seeking a highly skilled AI Platform Engineer to design, build, and operate our next-generation AI application platform. In this role, you will work on advanced AI systems including Retrieval-Augmented Generation (RAG) pipelines, multi-model gateways, Model Context Protocol (MCP) tools, agentic workflow automations (e.g., n8n), and secure chat interfaces such as OpenWebUI or custom-built solutions. 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. This role will work closely with product, data, and security teams to deliver scalable, secure, and high-performing AI-driven applications. Key Responsibilities - Design, develop, and operate the company’s AI application platform, including RAG pipelines, model gateways, MCP integrations, and agent workflows. - 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. - Collaborate cross-functionally with product, data science, engineering, and security to deliver high-impact AI features and integrations. - Troubleshoot production issues and continuously improve the platform’s architecture and performance. Required Skills & Qualifications - 4–10+ years of experience in software engineering, DevOps, or AI/ML platform engineering. - Strong hands-on programming experience in Python, Go, or TypeScript. - Expertise with Kubernetes, container orchestration, and cloud-native tooling. - Proficiency with Terraform, Helm, or other IaC frameworks. - Experience building RAG pipelines, LLM integrations, or similar AI workflows. - Familiarity with n8n, LangChain, OpenWebUI, or custom chat interface frameworks. - Solid understanding of observability tools (Prometheus, Grafana, ELK, OpenTelemetry). - Experience with secure, production-grade deployments of AI or distributed systems. 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.

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