2 months ago

Senior Forward Deployed Engineer, Applied AI

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 2 hours agoStatus: Live

Job Summary

Senior hands-on AI engineering role leading end-to-end enterprise AI programs on Cortex AI. You will mentor a small engineering team, define quality metrics for LLM/agent systems, and deliver scalable, production-ready AI solutions while collaborating with product, engineering and customer success teams. Travel up to ~25% to work onsite with strategic customers and drive AI initiatives from scoping through deployment.

Location: Menlo Park

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Key Responsibilities

•Lead complex, multi-engineer AI engagements from scoping and architecture through deployment, monitoring, and handoff, ensuring delivery quality and customer outcomes.
•Define what good looks like for each engagement by creating measurable quality metrics and evaluation frameworks; run systematic eval loops to improve agent quality.
•Provide day-to-day technical leadership and mentorship to a team of 2–6 Applied AI Engineers; review designs and code and develop team careers.
•Deliver high-quality ML pipelines and agentic AI solutions; translate ambiguous business objectives into robust, scalable, and performant implementations.
•Productionize AI at scale by managing end-to-end lifecycle including deployment, monitoring, and safety guardrails; close the loop from production feedback to evals.

Travel: Medium travel

Pay and Benefits

Salary: USD 200,000 - 270,000 annually

Key Requirements

•5+ years of professional software engineering experience.
•Demonstrated experience leading technical projects or teams, including setting technical direction, reviewing others' work, and driving delivery to completion.
•Proven experience building and productionizing applications using LLMs, especially with technologies like RAG and agentic workflows.
•Hands-on experience defining quality metrics and evaluation frameworks for LLM or agent systems, and using evals to systematically improve quality over time.
•Excellent problem-solving and communication skills, with an ability to articulate complex technical concepts to both technical and executive stakeholders.

Experience:5+ yearsEnterprise AILLMsAI engineering

Skills:CommunicationLeadershipProblem-solvingMentoringTeam leadership

Tech Stack:LLMsRAGEvalsLangSmithArizeWeavePromptfooPandasNumpySnowparkAWSAzureGCP

Company Brief

Snowflake

Provides a cloud-native data platform for data warehousing, data engineering, data science, and analytics, enabling organizations to store, process, and share large-scale data across multiple cloud providers with elastic scalability and performance.

Industry: Data Infrastructure

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Bozeman, United States

Founded: 2012

Website LinkedIn

Loading job details...

Preparing the role view and application actions.

Snowflake

2 months ago

Senior Forward Deployed Engineer, Applied AI

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 2 hours agoStatus: Live

Job Summary

Location: Menlo Park

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Key Responsibilities

•Lead complex, multi-engineer AI engagements from scoping and architecture through deployment, monitoring, and handoff, ensuring delivery quality and customer outcomes.
•Define what good looks like for each engagement by creating measurable quality metrics and evaluation frameworks; run systematic eval loops to improve agent quality.
•Provide day-to-day technical leadership and mentorship to a team of 2–6 Applied AI Engineers; review designs and code and develop team careers.
•Deliver high-quality ML pipelines and agentic AI solutions; translate ambiguous business objectives into robust, scalable, and performant implementations.
•Productionize AI at scale by managing end-to-end lifecycle including deployment, monitoring, and safety guardrails; close the loop from production feedback to evals.

Travel: Medium travel

Pay and Benefits

Salary: USD 200,000 - 270,000 annually

Key Requirements

•5+ years of professional software engineering experience.
•Demonstrated experience leading technical projects or teams, including setting technical direction, reviewing others' work, and driving delivery to completion.
•Proven experience building and productionizing applications using LLMs, especially with technologies like RAG and agentic workflows.
•Hands-on experience defining quality metrics and evaluation frameworks for LLM or agent systems, and using evals to systematically improve quality over time.
•Excellent problem-solving and communication skills, with an ability to articulate complex technical concepts to both technical and executive stakeholders.

Experience:5+ yearsEnterprise AILLMsAI engineering

Skills:CommunicationLeadershipProblem-solvingMentoringTeam leadership

Tech Stack:LLMsRAGEvalsLangSmithArizeWeavePromptfooPandasNumpySnowparkAWSAzureGCP

Company Brief

Snowflake

Industry: Data Infrastructure

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Bozeman, United States

Founded: 2012

Website LinkedIn