Forward Deployed Engineer, Frontier Engineering
- Level
- Mid
- Work type
- Remote
Not stated in the posting: salary, visa.
Open. First seen 23 October 2026.
About the role
Snowflake's standard text
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. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact.
We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done.
At Snowflake, we are building a high-impact team to help the world's most innovative companies unlock the power of AI. 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. You won't just work with cutting-edge technology – you'll deploy it to solve real-world business problems at scale, building production-grade AI systems using Snowpark, Cortex, and our native LLM capabilities.
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. Treat measurement as a first-class part of building, not an afterthought.
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, and close the loop from production traces and user feedback back into your evals so quality compounds over time.
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.
Snowflake's standard text
Snowflake is growing fast, and we’re scaling our team to help enable and accelerate our growth. We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and Snowflake.
How do you want to make your impact?
For jobs located in the United States, please visit the job posting on the Snowflake Careers Site for salary and benefits information: careers.snowflake.com
What this role asks for
Particular to this role
MLOps · NumPy · Pandas · RAG
Rare in Snowflake's other 216 open postings.
Standard for solutions / sales engineering roles
Python
Common in solutions / sales engineering postings at any company.
79% of this description is written for the role. The rest is Snowflake's standard text, folded away below.
Compared with Snowflake's other open jobs.
The team: Professional Services HIRES STEADILY
This role is one of 12 open in Professional Services. 7 were posted in the last 30 days and the oldest in March: a team that hires all year rather than one being built.
WHAT THE TEAM WORKS WITH, ACROSS ITS POSTINGS
Snowflake (12 of 12), Python (9 of 12), AWS (8 of 12), Generative AI (8 of 12), SQL (8 of 12), Azure (7 of 12), Data Warehousing (7 of 12)
OTHER ROLES ON THIS TEAM
- AI/ML Consulting Manager posted Oct 23
- Lead Forward Deployed Engineer - Migration posted Oct 22
- Principal Solutions Architect - Migrations posted Oct 19
- SNOWFLAKE FRONTIER ENGINEERING MANAGER, MIGRATIONS posted Oct 16
- Director, Product Management - Data Transformation (Frontier Engineering) posted Oct 14
- Sr. Engagement Manager, Frontier Engineering posted Oct 12
- AI Deployment Strategist posted Sep 21
- Sr. Manager, Technical Delivery posted Aug 28
- Principal Solutions Architect - Data Engineering posted Aug 25
- Principal Solutions Architect - AI/ML - Services Delivery posted Jul 2
- Solutions Architect posted Mar 9
From the team and dates on Snowflake's own job board.
Similar jobs
- Agentic AI Architect-Anthropic-US West at NewRocket
Shares 12 skills: NumPy, Pandas, MLOps… - Senior Data Scientist at Prominence Advisors
Shares 12 skills: NumPy, Pandas, MLOps… - Software AI Engineer at Devsinc
Shares 11 skills: NumPy, Pandas, MLOps… · same seniority - Data Scientist at Charger Logistics Inc
Shares 11 skills: NumPy, Pandas, MLOps… · same seniority - AI/ML Engineer (Sagacify) at craftzing
Shares 11 skills: NumPy, Pandas, MLOps… · same seniority - Director of Engineering, Frontier Engineering at Snowflake
Also at this company
Is this your posting? Email info@careerholo.com to have it removed.