AI/ML Architect

This is a fully remote position, open to applicants in United States.

📋 Description

• Architect and implement comprehensive AI/ML and Generative AI solutions from initial discovery to production deployment.

• Create production-grade RAG systems, vector search solutions, embedding pipelines, AI agents, copilots, and multi-agent workflows.

• Spearhead hands-on implementation utilizing Snowflake Cortex, Cortex Analyst, Cortex Search, Cortex Agents, Snowpark ML, and associated Snowflake AI technologies.

• Design scalable ML and LLM pipelines that facilitate training, inference, evaluation, monitoring, and governance.

• Integrate AI solutions with AWS, Azure, or GCP, alongside enterprise applications, APIs, ETL/ELT platforms, streaming systems, and third-party AI services.

• Establish reusable AI reference architectures, accelerators, technical standards, and governance frameworks.

• Offer technical leadership through architecture reviews, code evaluations, design sessions, and assessments for production readiness.

• Guide client discovery workshops, solution design, effort estimation, technical presentations, proof-of-concepts, and pre-sales activities.

• Collaborate with data engineers, ML engineers, application teams, architects, and business stakeholders throughout the delivery process.

⛳️ Requirements

• Over 10 years of experience in solution architecture, AI/ML architecture, enterprise architecture, or technical delivery.

• Strong recent hands-on experience in building and supporting production AI/ML and Generative AI solutions.

• Demonstrated experience with LLMs, RAG, vector databases, embedding pipelines, agentic AI, prompt engineering, and AI evaluation.

• Robust understanding of machine learning, deep learning, NLP, MLOps, and LLMOps.

• Practical experience with Snowflake Cortex, Cortex Analyst, Cortex Search, Cortex Agents, Snowpark ML, and Snowflake Native Apps.

• Significant architectural experience across Snowflake and at least one major cloud platform, preferably AWS or Azure.

• Experience with integrating AI platforms into APIs, microservices, SaaS applications, enterprise systems, Kafka, and event-driven architectures.

• Strong knowledge of AI security, governance, compliance, observability, and model monitoring.

• Exceptional client-facing communication, technical leadership, and stakeholder management skills.

• Capacity to balance strategic architecture ownership with hands-on technical execution.

🏝️ Benefits

• We assist enterprise organizations in transitioning from fragmented legacy systems to unified, AI-ready Snowflake platforms — achieving data migration, engineering, governance, BI & analytics, and AI/ML solutions 40–50% more efficiently than traditional methods.

• Over 450 Snowflake consultants, more than 200 enterprise transformations completed, and a dedicated 100% focus on Snowflake.

• Our clientele includes industries such as Financial Services, Healthcare & Life Sciences, Retail, Manufacturing, Energy, and more.