6 hours ago
Remote, New ZealandMid Level
Responsibilities
- Architect, build, and deploy enterprise-grade AI solutions and agents from prototype through production.
- Define quality metrics, evaluation frameworks, golden datasets, and systematic evaluation loops for AI and agent systems.
- Develop scalable Python and SQL applications and pipelines, including safety guardrails, observability, and human-review workflows.
- Own deployment, monitoring, optimization, and continuous quality improvement in secure, large-scale production environments.
- Partner directly with customer data science and engineering teams as a hands-on technical advisor.
- Share field learnings with Snowflake Product and Engineering teams to influence the AI platform.
- Spend at least 25% of working time onsite with strategic customers.
Requirements
- Bachelor’s degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
- At least 3 years of professional software engineering experience.
- Willingness to travel.
- Experience building applications using LLMs, RAG, and agentic workflows.
- Hands-on experience defining quality metrics, running evaluations, and systematically improving LLM or agent quality.
- Ability to communicate complex technical concepts to diverse stakeholders and solve ambiguous problems.
- Experience with production-trace and synthetic-data evaluation sets, A/B tests, ablations, or offline evaluations is preferred.
- Familiarity with Braintrust, LangSmith, Arize, Weave, Promptfoo, or custom evaluation harnesses is preferred.
- Experience analyzing failure modes in agent or RAG systems is preferred.
- Experience with the MLOps lifecycle, including model deployment, monitoring, and evaluation in AWS, Azure, or GCP, is preferred.
- Familiarity with pandas, NumPy, and Snowpark is preferred.
- Customer-facing technical experience, startup experience, and experience as a solutions architect, sales engineer, or professional services engineer are preferred.
Tech Stack
Categories
Forward Deployed
About Snowflake
Snowflake builds a cloud-native data platform used by enterprises to store, integrate, share, and analyze data across AWS, Azure, and Google Cloud. Its core products span data warehousing, data lakes, data engineering, and governed data sharing, sold via consumption-based subscriptions. Founded in 2012 and publicly traded on the NYSE (SNOW) following a 2020 IPO, Snowflake supports analytics and data application workloads across industries.