Large Language Model Architect
Ahmedabad
Posted 2d ago
Job Location
Ahmedabad
Tech Stack
Remote Work Policy
On-site
Categories
LLM Engineer
About the job
We are seeking a Large Language Model Architect to design and build advanced AI solutions. This role involves architecting large language models capable of processing and generating natural language, including designing neural network parameters trained on extensive unlabeled text data. You will own the complete AI platform architecture, integrating classical machine learning, generative AI, LLM applications, RAG, and agentic systems. This position requires operating at an executive and senior stakeholder level, translating business goals into a coherent technical vision and a sequenced AI implementation roadmap. Practical industry experience is essential to ensure AI architectures address domain realities, regulatory expectations, security constraints, and measurable business outcomes.
Responsibilities
- Lead and own the end-to-end technical solution for complex AI platforms, ensuring alignment with business objectives and enterprise standards.
- Define architectural direction for multi-agent systems, including orchestration, memory, tool/skill use, and AI gateway patterns.
- Establish the enterprise context layer architecture, covering knowledge graphs, vector search, semantic retrieval, and conversation state management.
- Set standards for security, governance, observability, performance, scalability, and reliability across AI solution domains.
- Mandate productized evaluation and observability practices for AI solutions.
- Drive architecture decisions for high-throughput, low-latency inference, model routing, and production-ready deployment platforms.
- Produce and own authoritative architecture artifacts, including blueprints, ADRs, and design specifications.
- Partner with stakeholders to shape enterprise AI strategy and convert business priorities into technical roadmaps.
- Lead enterprise AI architecture assessments, target-state definition, and gap analysis.
- Set the enterprise direction for Snowflake-native AI platforms, defining Cortex-based agent, RAG, and analytics architectures.
- Define Snowpark and Streamlit application reference patterns and establish standards for regulated AI workloads.
Requirements
- Bachelor's degree or equivalent in Computer Science, Computer Engineering, Data Science, AI/ML, Information Technology, or a related engineering discipline.
- Minimum 12+ years of overall experience in software engineering, data engineering, AI/ML engineering, cloud architecture, or enterprise technology architecture.
- Minimum 8+ years of experience designing and deploying enterprise-grade advanced AI, data, analytics, or cloud-native solutions using at least one cloud vendor.
- Minimum 2+ years of experience in LLM and generative AI solution architecture, including agentic AI, RAG, prompt engineering, model integration, and evaluation patterns.
- Minimum 2+ years of experience architecting and operationalizing LLM-driven application architecture patterns in production or enterprise-scale environments.
- Minimum 6+ years of experience in engineering, machine learning, deep learning, NLP solutions, data engineering, or large-scale analytical engineering applications.
- Demonstrated experience as a senior architect in industry domains such as banking, insurance, retail, healthcare, travel, logistics, or telecom.
- Deep architecture and hands-on engineering experience with Snowflake Cortex AI, Cortex Agents, Cortex Search, Snowpark, and Streamlit.
- Strong ability to shape enterprise-grade AI architecture covering RAG, embeddings, vector databases, semantic retrieval, context engineering, multi-agent orchestration, and GenAI evaluation.
- Experience defining NFRs and architecture controls for performance, scalability, security, privacy, governance, observability, resiliency, and cost optimization.
- Ability to compare platforms, frameworks, foundation models, and deployment patterns, making evidence-based technology recommendations.