AI/ML Consulting Manager

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.

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.

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