# Forward Deployed Engineer, Frontier Engineering **Company**: Snowflake **Location**: NZ-New Zealand-Remote **Work arrangement**: remote **Experience**: senior **Job type**: full-time **Category**: Engineering **Industry**: Technology **Apply**: https://jobs.ashbyhq.com/snowflake/e054c37d-8940-4cf6-b166-d5741991ad12?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply **Canonical**: https://yubhub.co/jobs/job_3a1036c5-612 ## Description At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. As a Forward Deployed Engineer on our Frontier Engineering team, you will be a hands-on builder and a key technical partner to our most strategic customers, placing you at the forefront of the enterprise AI revolution. ## IN THIS ROLE AT SNOWFLAKE, YOU WILL: ### Build Customer Solutions Architect, build, and deploy enterprise-grade AI solutions, including sophisticated AI agents. Own the end-to-end lifecycle of your workstreams – from prototype to production – directly solving customers' most complex business challenges. ### Own the Quality of What You Ship Define what "good" means for the systems you build. Translate ambiguous customer goals into measurable quality metrics, evaluation frameworks, and golden datasets – then run systematic eval loops to hill-climb on agent quality, catch regressions before customers do, and continuously raise the bar on accuracy, faithfulness, and safety. ### Deliver with Velocity Rapidly design, iterate, and ship high-quality code and pipelines. Translate ambiguous business objectives into robust, scalable, and performant solutions using Python and SQL. ### Productionize AI at Scale Own the full implementation lifecycle for your solutions – from prototype through deployment, monitoring, and optimization in secure, large-scale production environments. Build the safety guardrails, observability, and human-review workflows that keep AI applications reliable and trustworthy. ### Be a Technical Partner Partner directly with customer data science and engineering teams as a hands-on technical resource and trusted advisor on how to best leverage AI for their business challenges. ### Collaborate to Innovate Work cross-functionally with Snowflake's Product and Engineering teams, sharing real-world feedback from the field to directly influence the future of Snowflake's AI platform. ### Have the opportunity to travel Spend at least 25% of your time onsite, working closely with Snowflake's most strategic customers. ## WE'RE LOOKING FOR CANDIDATES WHO HAVE: ### Minimum Qualifications - Bachelor's degree in Computer Science, Engineering, a related technical field, or equivalent practical experience. - 3+ years of professional software engineering experience. - Willingness to travel. - Proven experience building applications using LLMs, especially with technologies like RAG and agentic workflows. - Hands-on experience defining quality metrics and running evaluations for LLM or agent systems, and using evals to systematically improve quality. - Excellent problem-solving and communication skills, with an ability to articulate complex technical concepts to diverse stakeholders. - Comfort with ambiguity and a desire to thrive in a fast-paced, ever-changing Generative AI environment. ### Preferred Qualifications - Experience building eval sets from production traces and synthetic data, and running structured experimentation (A/B tests, ablations, offline evals) to compare prompts, models, or agent architectures. - Familiarity with eval and observability tooling (e.g., Braintrust, LangSmith, Arize, Weave, Promptfoo) or experience building custom eval harnesses. - Experience with failure-mode analysis on agent or RAG systems – categorizing errors (hallucination, retrieval miss, planning failure, tool misuse) and driving each down with targeted evals. - Hands-on experience with the MLOps lifecycle, including model deployment, monitoring, and evaluation in a cloud environment (AWS, Azure, or GCP). - Familiarity with core data science libraries and tools (e.g., pandas, numpy, Snowpark). - Experience in a customer-facing technical role (e.g., solutions architect, sales engineer, or professional services). - Startup experience. ## Skills ### Required - LLMs - RAG - agentic workflows - Python - SQL - data science - engineering - AI ### Nice to have - eval sets - experimentation - observability tooling - MLOps - cloud environment - data science libraries --- Source: [Apply at jobs.ashbyhq.com](https://jobs.ashbyhq.com/snowflake/e054c37d-8940-4cf6-b166-d5741991ad12?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)