Senior Technical Architect
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Job Description
Senior Technical Architect delivering enterprise AI/ML solutions on Snowflake. Leading architecture, MLOps, and customer transformation across complex data platforms.
Responsibilities:
- Lead customer engagements as the primary technical authority, owning architecture decisions and measurable outcomes across complex, multi-workstream implementations
- Partner with customer executives and senior technical leadership to define platform strategy, long-term roadmaps, and alignment of Snowflake capabilities with business objectives
- Translate ambiguous business problems into scalable technical solutions with clear delivery paths and risk-mitigation strategies
- Serve as the technical escalation point, unblocking delivery teams and resolving architectural issues
- Architect and implement end-to-end AI/ML solutions on Snowflake
- Set standards for scalability, performance, security, and operability across customer environments
- Define and champion MLOps practices covering deployment pipelines, monitoring, governance, and lifecycle management
- Drive adoption of Snowflake's AI product suite, including Cortex, Streamlit in Snowflake, and Snowflake Intelligence
- Lead replatforming of complex AI/ML workloads onto Snowflake
- Coordinate across customer engineering, data science, and platform teams
- Bridge Services Delivery, Go-to-Market, and Snowflake product teams
- Channel customer feedback to influence product direction
- Mentor junior architects and consultants
- Contribute reusable architecture patterns, reference implementations, and delivery accelerators
Requirements:
- BA/BS in computer science, engineering, mathematics, or a related field, or equivalent practical experience
- 8+ years of experience in solutions architecture, technical consulting, data engineering, or a senior customer-facing technical role
- Track record leading architecture decisions on large-scale enterprise data and AI platforms
- Deep hands-on experience implementing Snowflake in production, including data modeling, performance tuning, security design, and platform governance
- Expert-level understanding of the data analytics stack, including ETL, data pipelines, data platform architecture, BI tooling, and semantic layers
- Strong understanding of the AI/ML lifecycle, including data preparation, feature engineering, model training, deployment, monitoring, and governance
- Proficiency in SQL and Python
- Ability to produce and review production-quality code
- Experience designing and implementing enterprise-scale MLOps frameworks and model lifecycle management
- Ability to influence senior technical and executive stakeholders and navigate complex organizational dynamics
- Hands-on experience with generative AI and LLM use cases in production is a bonus
- Experience building or scaling a Center of Excellence or establishing enterprise architectural standards is a bonus
- Background in a technology product company's services organization is a bonus
- AWS, Google Cloud, or Microsoft Azure advanced certifications are a bonus
- Snowflake SnowPro Advanced Certifications are a bonus
- Deep industry vertical expertise is a bonus
- Experience as a technical lead on multi-team or multi-vendor delivery programs is a bonus
Benefits:
- Bonus and equity plan eligibility
- Medical insurance
- Dental insurance
- Vision insurance
- Life insurance
- Disability insurance
- 401(k) retirement plan
- Flexible spending account
- Health savings account
- At least 12 paid holidays
- Paid time off
- Parental leave
- Employee assistance program
- Other company benefits
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