Principal Architect - AI

Responsibilities:

• Design AI system architectures, including RAG pipelines and agent frameworks.
• Evaluate and standardize AI platforms and tools.
• Oversee model development, validation, and production readiness.
• Ensure seamless integration with enterprise systems, APIs, and data platforms.
• Develop architectures catering to non-functional requirements like performance, reliability, security, usability, scalability, interoperability, and maintainability.
• Localization and Internationalization, Compliance, and Data Management.
• Write architectural design documents or review design documents.
• Communicate and coordinate with customers, partners, and internal stakeholders.

Requirements:

• Bachelor's/Master's degree in computer science or a related field from one of the premier institutes in India/Abroad. IIT/IIIT/ISI/RECs would be preferred.
• 10 - 15 years of experience, with 5+ years in AI technical and solution architecture.
• Strong expertise in ML, deep learning, and generative AI is a must.
• Deep expertise in integrating and training Large Language Models (LLMs), Large Multimodal Models (LMMs), and Small Language Models (SLMs).
• Proven experience deploying enterprise-scale agency AI systems, including Model Context Protocol (MCP) client-host architecture.
• Experience in agency calling and multimodal agents, including vernacular support for Indian languages, would be an added plus.
• In-depth understanding of AI governance and ethics.
• Experience in training or fine-tuning AI/ML models for real estate construction and BIM design solutions. Hands-on experience with AI agency calling, including Vernacular and English language support.
• Clear understanding of AI limitations and effective workarounds to avoid uncanny or inconsistent results and hallucinations.
• Experience performing AI-specific quality control, including fixing gesture issues, continuity problems, unnatural movements, and audio-visual mismatches.
• Ability to balance creative vision with technical constraints in fast-evolving AI environments.
• Knowledgeable in using CI/CD tools and DevOps technologies like Docker.
• Kubernetes and microservices with cloud environments like AWS/Azure/GCP
• Exposure to real estate technology platforms, including construction management, is preferred.
• Broad, operational knowledge of application servers, databases, load balancers, and other infrastructure components required to deploy web applications in a highly available and scalable environment.
• Acquainted with multiple SQL, NoSQL, vector, and graph database technologies such as MongoDB, Couchbase, Cassandra, Redis, Neo4j, Oracle, SQL Server, Qdrant, Milvus, Pinecone, ChromaDB, etc.
• A strong foundation in developing AI applications and products supporting desktop, mobile, and tablet is a must.
• Adapt to using design tools such as Diagrams.net, Lucidchart, PlantUML, Mermaid, etc.