---
title: 'AI/ML Consulting Manager at Snowflake'
canonical: 'https://feeny.ai/job/ai-ml-consulting-manager-snowflake-au-sydney-2e9d653zme7t'
type: 'job'
last_seen: '2026-10-23'
---

# AI/ML Consulting Manager at Snowflake

- **Company:** [Snowflake](https://feeny.ai/companies/snowflake)
- **Location:** Au-Sydney
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2026-10-23
- **Last confirmed live:** 2026-10-23
- **Apply:** https://jobs.ashbyhq.com/snowflake/be98e986-1fef-4ea9-8921-442137354ed8

## Job 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. 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.

We are hiring an AI/ML Consulting Manager for our Frontier Engineering team in Australia and New Zealand. Our team within Frontier Engineering helps customers take agents, machine learning models, and full stack applications from ideation to production and beyond, using Snowflake and its partner ecosystem. You will lead a team of technical architects and oversee partner resources delivering projects on Snowflake's behalf, helping both groups translate customer priorities into effective technical solutions and successful delivery.

This is a customer-facing leadership role with a utilisation target, primarily fulfilled through technical leadership and project oversight. You will guide architecture decisions, assess delivery quality, and help teams resolve complex challenges. You are not expected to be the primary hands-on builder, but you will bring the technical depth to challenge designs, review implementation approaches, and guide others toward the right outcomes.

AS AN AI/ML CONSULTING MANAGER AT SNOWFLAKE, YOU WILL:

- Lead, coach, and develop a team of technical architects across ANZ, setting clear expectations, supporting career growth, providing performance feedback, and building a collaborative team that shares expertise.
- Serve as a billable technical lead and delivery advisor across customer engagements, achieving a utilisation target through architecture guidance, technical reviews, project oversight, and customer advisory work.
- Own successful delivery of engagements by Snowflake architects and partner resources. Partner with customers and go-to-market teams to translate customer requirements into scoped engineering work, clear priorities, delivery milestones, and measurable acceptance criteria, balancing technical trade-offs with customer outcomes.
- Guide customers and delivery teams from problem definition and solution design through development, evaluation, deployment, and operational handover for AI agents and generative AI applications, including retrieval-augmented generation and integration with enterprise tools and workflows.
- Build trusted customer relationships through technical credibility, clear communication, and executive presence. Coordinate across customer stakeholders, project managers, architects, and partners; manage expectations, raise schedule and reliability risks early, and act as the manager-level escalation owner, de-escalating issues and driving resolution and follow-through.
- Coordinate team capacity and engagement assignments with delivery stakeholders, balancing customer commitments, technical fit, billable delivery, and time for coaching and professional development.
- Review solution designs and delivery quality, including grounding, safe tool use, security, governance, evaluation, and observability. Understand technical debt, including code health, test gaps, regressions, and support burden, and guide teams in prioritising remediation alongside new capabilities, with clear ownership and customer handover.
- Partner with Product Management, Engineering, and the wider Frontier Engineering organisation on planning, delivery dependencies, and customer feedback, creating opportunities for field insights to inform product priorities and reusable delivery practices. Travel to work with customers on-site up to 25% of the time.

OUR IDEAL AI/ML CONSULTING MANAGER WILL HAVE:

- 8+ years of relevant experience preferred in customer-facing technical consulting, solution architecture, or AI/ML delivery, with demonstrated responsibility for leading complex enterprise engagements.
- Experience managing and developing technical professionals, including coaching, performance management, career development, and creating an environment where people can raise risks and learn from each other.
- Experience taking accountability for customer outcomes across internal and partner delivery teams, translating customer needs into actionable engineering plans, coordinating stakeholders and resources, and resolving escalations through sound technical judgement and clear communication.
- A thorough understanding of the generative AI application development lifecycle, including use case framing, model selection, prompt and context design, agent orchestration, tool integration, and evaluation, supported by experience guiding production delivery.
- Strong understanding of production practices for LLM applications and AI agents, including evaluation and regression testing, deployment, observability, guardrails, human oversight, and reliability, along with knowledge of traditional ML and MLOps best practices.
- Cloud architecture knowledge and experience with at least one public cloud platform, such as AWS, Azure, or Google Cloud, with the ability to assess how Snowflake and complementary technologies fit customer requirements.
- A practical technical foundation in Python, APIs, and frameworks for building LLM applications and AI agents, with the design and code-review judgement to coach architects, recognise technical debt and test gaps, and balance delivery speed, maintainability, and ongoing support cost without being the primary developer on every engagement.
- Clear communication with technical and executive audiences, sound judgement in managing customer expectations and delivery trade-offs, and a degree in computer science, engineering, mathematics, or a related field, or equivalent experience.

## BONUS POINTS FOR THE FOLLOWING:

- Experience guiding delivery of generative AI applications and AI agents on Snowflake, including integration with enterprise data, APIs, and complementary tools in its partner ecosystem.
- Experience improving consulting delivery through reusable architecture patterns, evaluation approaches, and AI-assisted workflows.
- Experience with agent orchestration frameworks, retrieval and vector search, or evaluation tools for generative AI applications, with additional experience in data science and traditional machine learning welcomed.
- Industry expertise in areas such as financial services, retail, or manufacturing, with the ability to connect technical decisions to customer priorities.

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](http://careers.snowflake.com)

## About Snowflake

## Company Overview
- **One-liner**: Snowflake provides an AI Data Cloud platform that enables enterprises to store, analyze, and securely share their data across multiple clouds and geographies.
- **Entity Type**: Public (NYSE: SNOW)
- **Headquarters**: Bozeman, Montana, United States
- **Founded**: 2012
- **Founders**: Not explicitly listed in the provided search results (widely known co-founders include Benoit Dageville, Thierry Cruanes, Marcin Zukowski – not verified in these search results)

## Core Business
- **Primary Industry**: Enterprise software, cloud data platform
- **Target Customers**: B2B, including large enterprises (e.g., hundreds of the world’s largest companies), mid-market, and SMBs
- **Mission**: “To Mobilize the World’s Data” (Glassdoor) and “empower every enterprise to achieve its full potential through data and AI” (Snowflake Careers page)

## Products & Services
- **Snowflake AI Data Cloud**: A unified, multi-cloud platform that combines data warehousing, data lakes, data sharing, and AI/ML capabilities. Customers can discover, share, and analyze data while running analytic workloads across public clouds (AWS, Azure, GCP).
- **Snowflake Marketplace**: A marketplace for discovering and accessing third‑party data sets and applications.
- **Snowflake‑Powered Applications**: Platform for building and deploying data‑intensive applications.

## Market Standing
- **Valuation/Market Cap**: Not directly provided in search results (as a public company, market cap fluctuates and is available on financial websites).
- **Key Metric**: Annual Revenue – $1 to $5 billion (USD) per Glassdoor.
- **Notable Investors/Partners**: Not explicitly mentioned in the search results (historically backed by Sequoia Capital, Dragoneer, etc. – not verified here).
- **Growth Signals**:
  - Named #1 on the 2023 Fortune Future 50 List ([Fortune.com](https://fortune.com))
  - Listed as a U.S. Best Large Place to Work by BuiltIn in 2024
  - Recognized as one of the “20 Coolest Cloud Software Companies” by CRN in 2022 and 2024
  - Headcount of 5,001–10,000 employees with 30 global locations; actively hiring
  - Revenue range $1B–$5B indicates strong scale

## Competitive Advantages
- **Multi‑Cloud Flexibility**: Operates across AWS, Azure, and GCP, avoiding vendor lock‑in.
- **Unified Data Experience**: One platform for data sharing, analytics, and AI, reducing silos.
- **Separation of Compute and Storage**: Allows independent scaling and cost efficiency (not detailed in provided sources, but a known differentiator).
- **Strong Ecosystem**: Data marketplace and extensive partner network.

## Strategic Focus
- **AI & Data Innovation**: The company’s current emphasis is on making “enterprise AI easy, efficient, and trusted” and integrating AI capabilities into the Data Cloud.
- **Global Expansion**: Active hiring across 30 locations indicates continued geographic growth.
- **Customer‑Centric Development**: Focus on empowering enterprises to achieve “full potential through data and AI.”

## Why Work Here
- **Culture**: Described as “driven by innovation, low egos, high bars, and collaboration” (Snowflake Careers page). Glassdoor rating of 3.9/5 overall (78% approve CEO).
- **Work‑Life Balance**: Glassdoor rates Work/Life Balance at 3.7/5; many remote and hybrid roles available (see Indeed listings).
- **Benefits**: “Benefits & Beyond” program includes competitive compensation, equity, career advancement programs, and commitment to pay equality and veteran hiring.
- **Engineering Focus**: Hiring process includes 2–4 week timeline with technical interviews; the company values impactful, project‑based work for all roles, including interns.
- **Recognition**: Named a Best Large Place to Work (BuiltIn 2024) and future‑focused by Fortune, signaling strong employer brand.

## Sources
1. [Snowflake Careers Overview](https://careers.snowflake.com/us/en)
2. [Life at Snowflake](https://careers.snowflake.com/us/en/snowflake-life)
3. [Snowflake on Glassdoor](https://www.glassdoor.com/Overview/Working-at-Snowflake-EI_IE928471.11,20.htm)
4. [Snowflake Hiring Process](https://careers.snowflake.com/us/en/gethired)
5. [Snowflake on Indeed](https://www.indeed.com/cmp/Snowflake-7f4a7fba)
6. [Snowflake Careers Portal (Ashby)](https://jobs.ashbyhq.com/snowflake) – provided by user

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