Large Language Model Architect _ Snowflake

Lecan Solutions; Hyderabad, Pune District, Bengaluru; Hybrid; INR 5,000,000 - 8,000,000; Full time

Job summary

Lecan Solutions seeks an experienced Large Language Model Architect for Snowflake to own KG lifecycle, ingest, modeling, curation, and deployment. You will work with Knowledge Engineering, Generative AI, LLMs, and multi-modal models, shaping ontology design and evaluation.

Lead architectural strategies for LLMs, mentor the team, and coordinate cross-functional efforts to integrate language models into broader systems for enterprise-scale applications.

Qualifications

• Extensive knowledge graph development lifecycle experience.
• Hands-on experience with LLMs and multi-modal models.
• Strong design, evaluation, and maintenance of ontologies.

Responsibilities

• Lead KG components and architecture for client data projects.
• Design and implement AI and semantic solutions.
• Collaborate with engineering, research, and product teams.
• Mentor team members and support sales when needed.
• Drive LLM architecture development and integration efforts.

Skills

Knowledge Graphs

Snowflake

LLMs

TensorFlow

PyTorch

Python

NLP

Data Modeling

Architectural design

Cloud platforms

Education

Bachelor's degree

15 years full-time education

Tools

RDF

SPARQL

LPG

SHACL

Snowflake Data Warehouse

Neo4J

Graph databases

Job description

Job Title: Large Language Model Architect Snowflake

Location:PAN INDIA

Experience: 5+ Years

Educational Qualification: 15 Years Full-Time Education

Job Summary

We are looking for a strong individual contributor Knowledge Engineer growing into a team lead role. The candidate should be well versed in the full Knowledge Graph development lifecycle and able to formulate real-world problems into practical, efficient, and scalable AI and Knowledge Graph solutions.

The role involves hands‑on work across the lifecycle from ingestion through modeling, curation, and deployment. The candidate will work with Knowledge Engineering, Generative AI, LLM, and multi‑modal models and contribute to ontology design, evaluation, and maintenance.

Key Responsibilities

• Build Knowledge Graph components that contribute to transforming a client's data architecture.
• Design, develop, and implement AI and semantic solutions.
• Ensure solutions integrate cleanly with the broader system.
• Work alongside the project team and delivery leads.
• Build strong working relationships with client counterparts.
• Help assemble supporting evidence for the recommended semantic layer solution.
• Support sales efforts when required.
• Continue developing skills in Data & AI solutions, especially agentic technologies, and share knowledge with the team.
• Lead the development and implementation of architectural strategies for Large Language Models.
• Facilitate knowledge sharing and mentorship within the team.
• Coordinate cross‑functional efforts to ensure seamless integration of language models into broader systems.

Must Have Skills

• Snowflake Data Warehouse
• Minimum 5 years of experience in Snowflake Data Warehouse.
• Strong understanding of data warehousing concepts and cloud‑based data storage solutions.
• Experience in designing scalable data architectures to support machine learning workloads.
• Familiarity with data processing pipelines and optimization techniques for large datasets.
• Ability to analyze and troubleshoot complex data integration and performance issues.

Good to Have Skills

• Microsoft Azure Data Services
• Data Science
• Knowledge Graph technologies
• RDF, SPARQL, LPG, SHACL
• Schema design, ontology management, and KG curation
• Graph‑based ML models
• Relational databases, object stores, graph databases and vector databases
• AWS, Azure, GCP
• Python
• TensorFlow, PyTorch
• Apache NiFi, Airflow
• NLP and Search techniques
• Prompt Engineering
• LLMs for enterprise‑scale applications
• Agentic systems

Required Experience

• Minimum 2 years of experience with Knowledge Graph technologies such as RDF, SPARQL, LPG, SHACL.
• Minimum 2 years of experience in schema design, ontology management, and KG curation.
• Minimum 2 years of experience designing and developing KG solutions and graph‑based ML models.
• Minimum 1 year of experience with end‑to‑end data pipeline implementation for AI applications, especially LLMs.
• Minimum 2 years of experience with relational databases, object stores, graph databases such as Stardog, Neo4J, Amazon Neptune, and vector databases.
• 2+ years of hands‑on experience with cloud platforms such as AWS, Azure, or GCP.
• 2+ years of experience in Python, with frameworks such as TensorFlow and PyTorch.
• Experience with ETL pipeline tools such as Apache NiFi and Airflow.
• Practical experience with NLP and/or Search techniques.
• Experience with Prompt Engineering and LLMs for enterprise‑scale applications.
• Team lead experience.
• Strong collaboration skills across engineering, research, and product teams.
• External client‑facing consulting experience.
• Broad experience in diverse ML techniques and agentic systems.

Roles & Responsibilities

• Expected to be an SME and collaborate with and manage the team.
• Responsible for team decisions.
• Engage with multiple teams and contribute to key decisions.
• Provide solutions to problems for the immediate team and across multiple teams.
• Lead LLM architecture development and implementation.
• Support knowledge sharing and mentorship.
• Coordinate cross‑functional efforts for seamless integration of LLM solutions.

Education

• Bachelor's degree or equivalent.
• 15 years of full‑time education is required.