Large Language Model Architect

Role overview: The Large Language Model Architect is a senior AI/LLM technology architecture engineer responsible for designing and delivering enterprise-grade LLM and generative AI platform architectures (Snowflake-native and cloud) and acting as technical authority across architecture domains (agentic application design, AI security & trust, AI operations/observability, data/knowledge engineering, model platforms and inference). The posting is for a Full-time position based in Chennai. Key responsibilities: - Define technical vision, architecture blueprints, non-functional requirements and implementation roadmaps that translate business strategy into delivery plans. - Lead stakeholder workshops to align on feasibility, scope, solution boundaries, dependencies and client expectations. - Design Snowflake-native AI application architectures (Cortex-based agents, RAG, document intelligence, Snowpark and Streamlit patterns) and establish RBAC, masking, lineage, monitoring, cost controls and governance for regulated GenAI workloads. - Architect model- and tool-agnostic multi-agent systems (orchestration, tool use, agent memory, context management, MCP/control-plane patterns and reusable service abstractions). - Design end-to-end data and context layers: ingestion, preprocessing, synchronization, chunking, embeddings, vector search, knowledge graphs and semantic retrieval to enable RAG. - Define evaluation frameworks for accuracy, relevance/faithfulness, latency, cost, safety and operational reliability; establish AI security, governance and observability controls (guardrails, prompt-injection defenses, PII protection, access control, audit logging, tracing). - Maintain architecture decision records, component and sequence diagrams, design specs, integration patterns and reusable reference assets. Required qualifications and experience (as stated): - Bachelor's degree or equivalent in CS, Computer Engineering, Data Science, AI/ML, IT or related engineering discipline; the posting also references "15 years full time education." - The job lists experience ranges including "Experience: 10-12 years" and elsewhere notes "Minimum 12 year(s) of experience is required." The requirements detail: minimum 10+ years in software/data/AI engineering or architecture; minimum 5+ years designing/deploying enterprise-grade advanced AI or cloud data solutions; minimum 2+ years in agentic AI/LLM/generative AI architecture or delivery; minimum 4+ years coding in Python and working with APIs, distributed systems and cloud-native patterns; minimum 4+ years in ML, deep learning, NLP, data engineering or AI product delivery. Required technical skills and tools: - Hands-on experience with Snowflake features and Cortex stack (Cortex AI, Cortex Agents, Cortex Search, Cortex Analyst, Cortex AI/LLM Functions), Snowpark, Streamlit, Dynamic Tables, Tasks, Streams and Snowflake ML. - Deep knowledge of LLM architecture patterns including RAG, embeddings, vector DBs, prompt engineering, model routing, fine-tuning/adaptation, function calling, tool integration and agent orchestration. - Experience defining enterprise AI platform patterns for performance, scalability, security, reliability, observability, governance and cost optimization; CI/CD, IaC, automated testing, model evaluation, MLOps/LLMOps, monitoring and production release governance. Good-to-have / preferred: - SnowPro certifications, Snowpark Python, semantic models, dbt, Native Apps, data sharing, Cortex Guardrails and Snowflake cost/performance tuning. - Familiarity with open-source orchestration and LLM tooling such as LangChain, LangGraph, LlamaIndex, Haystack, Semantic Kernel, MLflow, FastAPI, Docker and Kubernetes. - Experience with responsible AI practices: model risk management, AI governance boards, red-teaming, human-in-the-loop review, A/B testing and GenAI FinOps. Location & additional notes: - Position listed for Chennai, India. Employment type: Full-time. The posting emphasizes domain-grounded solutions for industries such as banking, insurance, retail, healthcare, travel, logistics or telecom. The role expects strong stakeholder communication skills and prior solution/technology architect experience in industry contexts.