Large Language Model Architect _ Snowflake

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.