Large Language Model Architect
Coimbatore
Posted 2d ago
Job Location
Coimbatore
Tech Stack
Remote Work Policy
On-site
Categories
LLM Engineer
About the job
We are seeking an experienced Large Language Model Architect to join our AI LLM Technology Architecture team. This hands-on engineering role focuses on designing, building, integrating, testing, and operationalizing enterprise-grade LLM, GenAI, and agentic AI components for client engagements. You will own platform-specific engineering on Snowflake, translating high-level architecture into production-quality components for LLM-driven applications, RAG pipelines, multi-agent workflows, and AI platform integrations. Bringing practical industry experience, you will identify domain data, process constraints, and adoption risks while designing safe, scalable, and relevant GenAI solutions. As a technical lead, you will contribute code, design decisions, reusable patterns, and engineering documentation.
Responsibilities
- Design and build LLM application components including prompts, tools, agents, orchestration flows, memory/context handling, retrieval pipelines, and evaluation harnesses.
- Develop Cortex-powered LLM applications and agents within the Snowflake security perimeter, building RAG and document intelligence using Cortex Search and Cortex AI Functions.
- Integrate Streamlit/Snowpark applications, applying RBAC, masking, lineage, and monitoring for regulated enterprise use cases.
- Implement data ingestion, parsing, chunking, enrichment, embeddings, vector search, and retrieval workflows for structured and unstructured enterprise content.
- Engineer safety and control components including PII detection/redaction, prompt-injection defenses, content filters, guardrails, authentication, authorization, lineage, and audit logging.
- Collaborate with architects, data engineers, product owners, and security stakeholders to convert solution designs into tested, observable, and maintainable software components.
- Maintain technical artifacts such as component designs, integration specifications, deployment runbooks, evaluation results, and reusable engineering patterns.
Requirements
- Bachelor's degree in Computer Science, Computer Engineering, Data Science, AI/ML, Information Technology, or a related engineering discipline.
- Typically 5+ years of software/data/AI engineering experience, including 2+ years in cloud-native engineering and 1+ year in GenAI, LLM, NLP, or agentic AI delivery.
- Hands-on coding experience in Python and strong understanding of APIs, distributed systems, CI/CD, testing, observability, and secure SDLC practices.
- Experience delivering AI/ML or data products in at least one industry domain such as banking, insurance, retail, healthcare, travel, logistics, or telecom.
- Hands-on experience with Snowflake Cortex AI, Cortex Agents, Cortex Search, Cortex Analyst, Cortex AI Functions/LLM Functions, Snowpark, Streamlit in Snowflake, Dynamic Tables, Tasks, Streams, Snowflake ML, RBAC, masking policies, and observability.
- Strong understanding of LLM application architecture patterns including RAG, function/tool calling, agent orchestration, model invocation, prompt engineering, embeddings, vector databases, and evaluation metrics.
- Ability to implement traditional ML and GenAI components across ingestion, feature/data preparation, model integration, deployment, monitoring, and continuous improvement.
- Practical knowledge of security, privacy, governance, performance, scalability, reliability, and cost controls for production AI systems.
- Experience with Git-based development, automated testing, CI/CD pipelines, infrastructure-as-code, and agile delivery in client-facing environments.