Title: Platform Architect — GenAI/LLM Systems Location: Hyderabad Experience: 7+ Years Employment Type: Full-Time | Immediate Start About the Role We are seeking a skilled and passionate Platform Architect – GenAI/ LLM Systems to join our team. What You’ll Do Architect scalable, cloud-native infrastructure to support enterprise-grade GenAI and LLM-powered applications. Design and deploy secure, reliable API gateways, orchestration layers (Airflow, Kubeflow), and CI/CD workflows for ML and LLM pipelines Collaborate with data and ML engineering teams to enable low-latency LLM inference and vector-based search platforms across GCP (or multi-cloud) Define and implement a semantic layer and data abstraction strategy to enable consistent and governed consumption of data across LLM and analytics use cases. Implement robust data governance frameworks including role-based access control (RBAC), data lineage, cataloging, observability, and metadata management. Guide architectural decisions around embedding stores, vector databases, LLM tooling, and prompt orchestration (e.g., LangChain, LlamaIndex) Establish compliance and security standards to meet enterprise SLA, privacy, and auditability requirements. What Sets You Apart 7+ years of experience as a Platform/Cloud/Data Architect, ideally within GenAI, Data Platforms, or LLM systems. Strong cloud infrastructure experience on GCP (preferred), AWS, or Azure, including Kubernetes, Docker, Terraform/IaC. Demonstrated experience building and scaling LLM-powered architectures using OpenAI, Vertex AI, LangChain, LlamaIndex, etc. Familiarity with semantic layers, data catalogs, lineage tracking, and governed data delivery across APIs and ML pipelines. Track record of deploying production-grade GenAI/LLM services that meet performance, compliance, and enterprise integration requirements. Strong communication and cross-functional leadership skills — ability to translate business needs into scalable architecture
As a skilled and passionate Platform Architect specializing in GenAI/LLM Systems, you will be responsible for architecting scalable, cloud-native infrastructure to support enterprise-grade GenAI and LLM-powered applications. Your role will involve designing and deploying secure, reliable API gateways, orchestration layers (such as Airflow, Kubeflow), and CI/CD workflows for ML and LLM pipelines. Collaboration with data and ML engineering teams will be essential to enable low-latency LLM inference and vector-based search platforms across GCP (or multi-cloud). You will define and implement a semantic layer and data abstraction strategy to facilitate consistent and governed consumption of data across LLM and analytics use cases. Additionally, implementing robust data governance frameworks including role-based access control (RBAC), data lineage, cataloging, observability, and metadata management will be part of your responsibilities. Your role will involve guiding architectural decisions around embedding stores, vector databases, LLM tooling, and prompt orchestration (e.g., LangChain, LlamaIndex), as well as establishing compliance and security standards to meet enterprise SLA, privacy, and auditability requirements. To excel in this role, you should have at least 7 years of experience as a Platform/Cloud/Data Architect, ideally within GenAI, Data Platforms, or LLM systems. Strong cloud infrastructure experience on GCP (preferred), AWS, or Azure, including Kubernetes, Docker, Terraform/IaC is required. Demonstrated experience in building and scaling LLM-powered architectures using OpenAI, Vertex AI, LangChain, LlamaIndex, etc. will be a significant advantage. You should also have familiarity with semantic layers, data catalogs, lineage tracking, and governed data delivery across APIs and ML pipelines. A track record of deploying production-grade GenAI/LLM services that meet performance, compliance, and enterprise integration requirements is essential. Strong communication and cross-functional leadership skills are also desired, as you will be required to translate business needs into scalable architecture.,