Remote AI/ML Architect — Snowflake Cortex & GenAI

Vekend, Llc

Northern (KY)

Hybrid

USD 140,000 - 190,000

Full time

18 hours ago

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Benefits offered by this job

Medical, dental, vision insurance

401(k) with company match

Paid time off

Flexible work arrangements

Job summary

Vekend, Llc seeks an experienced AI/ML Engineer to lead the design and implementation of enterprise-grade conversational AI solutions. You will architect intelligent applications using Snowflake Cortex, RAG, and Agentic AI frameworks, delivering secure, scalable AI for Sales, Marketing, Product, and Executives across a remote US environment.

The role demands hands-on experience with Cortex Complete, Cortex Agents, CoWork, and integration with enterprise tools, SQL, and APIs.

Qualifications

8+ years of experience in AI/ML, Data Engineering, or Data Platforms.
Minimum 2+ years building production-grade Generative AI or LLM-based applications.
Experience delivering enterprise AI solutions on Snowflake.
Hands-on experience designing, developing, deploying, and evaluating Agentic AI applications is required.

Responsibilities

Design and implement enterprise-scale Generative AI solutions using Snowflake Cortex native capabilities.
Define AI architecture, knowledge retrieval strategies, embedding models, chunking techniques, and semantic search patterns.
Build scalable, secure, and governed AI applications following enterprise best practices.
Develop AI applications using Cortex Complete, Cortex Search, Cortex Analyst, Cortex Agents, Cortex AI Functions, and CoWork.
Leverage Snowflake native AI capabilities to build intelligent assistants and business copilots.
Design and optimize advanced RAG pipelines.
Implement hybrid search combining semantic and keyword retrieval.
Develop chunking, indexing, re-ranking, and context optimization strategies to maximize response quality.
Design, develop, and deploy autonomous AI agents using Cortex Agents.
Build Planner–Tool–Executor–Refiner workflows capable of solving complex, multi-step business problems.
Integrate AI agents with enterprise tools, SQL, APIs, and business workflows.
Evaluate, optimize, and monitor agent performance for accuracy, reliability, and business outcomes.
Develop reusable prompt libraries and system prompts.
Optimize prompts for accuracy, consistency, latency, and business relevance.
Utilize Snowflake AI functions for summarization, classification, translation, sentiment analysis, and information extraction.
Design and implement AI evaluation frameworks using LLM-as-a-Judgemethodologies.
Measure faithfulness, relevancy, groundedness, toxicity, hallucination, response quality, and Agentic AI performance.
Implement Cortex Guardrails and Responsible AI practices to ensure secure, trustworthy AI responses.
Deploy AI applications across development, testing, and production environments.
Implement CI/CD pipelines and deployment automation for Snowflake AI solutions.
Ensure governance, monitoring, observability, access controls, and lifecycle management of AI applications.
Optimize inference performance, latency, and Snowflake credit consumption.
Monitor AI workloads and implement strategies for efficient compute utilization.
Design cost-effective AI architectures without compromising user experience.