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Core Architect
Location
India
Posted
69 days ago
Salary
0
Seniority
Mid Level
Job Description
Core Architect
Weekday (YC W21)
Role Description We are seeking an experienced Core Architect to define and drive the technical architecture, engineering standards, and long-term technology strategy for advanced AI-powered platforms. In this role, you will lead multiple engineering teams responsible for AI infrastructure, model orchestration, vector knowledge systems, and developer tooling. The ideal candidate will combine deep expertise in distributed systems, AI infrastructure, and cloud-native platforms with strong leadership capabilities to guide engineering teams and deliver scalable, production-ready GenAI solutions. Key Responsibilities - Platform Architecture & Technical Leadership - Define and own the overall architectural vision across data ingestion, vector retrieval, orchestration, inference, and developer tooling. - Establish engineering standards, design patterns, and best practices for building scalable AI platforms. - Lead architecture discussions and design reviews across engineering teams. - AI Systems & Workflow Design - Architect agentic workflows using modern frameworks such as MCP, LangGraph, CrewAI, and related orchestration systems. - Design and optimize retrieval systems, vector knowledge architectures, and multi-tool AI pipelines. - Build scalable frameworks for integrating embeddings, vector databases, and Retrieval-Augmented Generation (RAG) systems. - Engineering Leadership & Mentorship - Lead and mentor engineers across machine learning, AI application development, and full-stack engineering teams. - Provide technical guidance on system scalability, performance optimization, and architecture decisions. - Platform Reliability & Cloud Infrastructure - Define best practices for MLOps, observability, monitoring, and cost optimization across AI platforms. - Architect secure, cloud-native deployments across multiple regions using modern infrastructure frameworks. - Ensure systems meet reliability, scalability, and operational standards. - Cross-Functional Collaboration - Work closely with product, data, and research teams to convert experimental GenAI concepts into production-ready solutions. - Align architecture decisions with product roadmaps and business goals. Qualifications - 10–15+ years of experience in distributed systems, platform engineering, or large-scale infrastructure architecture. - Deep expertise in AI frameworks, vector databases, embeddings, and Retrieval-Augmented Generation (RAG) systems. - Proven experience leading architecture initiatives and scaling complex platforms. Technical Expertise - Strong proficiency with LangChain, LlamaIndex, and related AI orchestration frameworks. - Hands-on experience with vector databases, embeddings, and AI retrieval architectures. - Experience with agentic frameworks and orchestration tools. - Deep expertise in cloud-native environments including AWS, Azure, Kubernetes, and containerized platforms. - Familiarity with Kafka, Terraform, and observability systems for distributed architectures. Key Skills - AI Platform Architecture - LangChain / LlamaIndex - Vector Databases & RAG Systems - Distributed Systems Design - Cloud-Native Infrastructure (AWS / Azure / Kubernetes) - Kafka & Terraform - MLOps & Observability - Scalable AI System Design
Job Requirements
- 10–15+ years of experience in distributed systems, platform engineering, or large-scale infrastructure architecture.
- Deep expertise in AI frameworks, vector databases, embeddings, and Retrieval-Augmented Generation (RAG) systems.
- Proven experience leading architecture initiatives and scaling complex platforms.
- Technical Expertise
- Strong proficiency with LangChain, LlamaIndex, and related AI orchestration frameworks.
- Hands-on experience with vector databases, embeddings, and AI retrieval architectures.
- Experience with agentic frameworks and orchestration tools.
- Deep expertise in cloud-native environments including AWS, Azure, Kubernetes, and containerized platforms.
- Familiarity with Kafka, Terraform, and observability systems for distributed architectures.
- Key Skills
- AI Platform Architecture
- LangChain / LlamaIndex
- Vector Databases & RAG Systems
- Distributed Systems Design
- Cloud-Native Infrastructure (AWS / Azure / Kubernetes)
- Kafka & Terraform
- MLOps & Observability
- Scalable AI System Design
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