Job Details

Job Title: GenAI + Snowflake Cortex Architect (Remote)
Location: Remote
6+ Months Contract

About the Role
We are seeking a seasoned Architect to lead the design, development and deployment of generative-AI enabled data/analytics solutions built on the Snowflake Data Cloud and Snowflake Cortex platform. This person will bridge the worlds of data engineering, ML/AI (especially GenAI and LLMs), and Snowflake architecture to deliver next-generation, production-grade systems.
You will be responsible for shaping the end-to-end architecture: from ingestion, transformation and storage on Snowflake, to embedding generative AI (LLMs, retrieval-augmented generation, agents) via Snowflake Cortex (including Cortex Analyst, Cortex Search, Cortex Agents). You'll work with cross-functional teams (data engineers, ML/AI engineers, product, business stakeholders) and guide the solution from proof-of-concept through to production.

Don't need profile on Data side, client need more into GenAI...
Previous Data side experience is fine, but client need current experience more into GenAI

Key Responsibilities

• Define and own the architecture for GenAI use-cases leveraging Snowflake + Snowflake Cortex (structured & unstructured data, semantic models, vector search, RAG, agents).
• Design and implement Snowflake data platform components: data lake/warehouse, ingestion (batch/stream), transformation, storage, compute (virtual warehouses), Snowpark, dynamic tables, etc.
• Establish semantic models, YAML definitions, and conversational layers using Cortex Analyst for natural language to SQL and business-user self-service insights. Snowflake Documentation+2snowflake.com+2
• Build retrieval and semantic search over unstructured content using Cortex Search and vector embeddings (via Snowflake or integrated vector/database technologies). Atlan+1
• Develop and deploy Agent workflows (Cortex Agents) orchestrating structured & unstructured queries, LLMs, tool invocation, multi-modal data. Snowflake Documentation+1
• Work closely with ML/AI teams and data scientists to integrate GenAI/LLM models (open source or commercial - e.g., GPT, Claude) and embed them into the Snowflake platform.
• Optimize performance, cost, and scalability: Snowflake warehouse sizing, micro-partitioning, clustering, cost control, query tuning, governance, security (RBAC, masking, row-level security). Apna+1
• Drive POCs, prototyping, build accelerators/reference architectures for GenAI+Snowflake scenarios, and evangelize best practices internally and externally.
• Provide advisory and pre-sales support (solutioning, estimations, client workshops) where required.
• Ensure proper governance, data security, compliance (GDPR, HIPAA, internal policy) in GenAI context: data movement minimisation, privacy, auditability. Atlan+1
• Mentor and lead teams, create knowledge base and best practice libraries around GenAI and Snowflake Cortex.

• Bachelor's or Master's in Computer Science, Data Engineering, Machine Learning, or related field.
• 8-15+ years of professional experience in data/analytics architecture, of which at least 3-5 years in a solution architect role involving Snowflake and/or GenAI.
• Strong expertise in Snowflake: data warehousing, ELT/ETL, Snowpark (Python/Scala), Snowflake features (Streams, Tasks, Dynamic Tables, Micro-Partitioning, Clustering, Zero-Copy Cloning, Data Sharing).
• Hands-on with GenAI/LLMs: embedding generation, vector search, RAG pipelines, prompt design, agent orchestration.
• Familiarity with Snowflake Cortex platform: Cortex Analyst, Cortex Search, Cortex Agents. Snowflake Documentation+1
• Proficiency in SQL (advanced), Python (or equivalent), and knowledge of AI/ML frameworks and libraries.
• Cloud experience (AWS, Azure or GCP) integrating with Snowflake and GenAI workloads.
• Experience with building semantic models, conversational interfaces, business user self-service analytics.
• Strong communication and stakeholder management skills - able to translate business requirements into technical solutions.
• Proven track record of delivering scalable data + AI solutions in production.
• Certifications (nice to have): SnowPro Core/Advanced, Snowflake Architect, or equivalent.

• Experience with hybrid data (structured + unstructured) and building document-intelligence or chatbots using GenAI over enterprise data.
• Experience integrating Snowflake with vector database technologies or knowledge graph solutions.
• Experience with MLOps/ModelOps, CI/CD pipelines, model monitoring & retraining.
• Exposure to domain knowledge (financial services, healthcare, manufacturing) where GenAI + data platforms are applied.
• Previous experience leading pre-sales engagements, client workshops, solutioning efforts for GenAI/AI-at-scale.