AI/ML Consulting Manager

About the role

Snowflake is hiring an AI/ML Consulting Manager for its Frontier Engineering team, which helps customers take agents, machine learning models and full-stack applications from ideation to production using Snowflake and its partner ecosystem. This is a customer-facing leadership role with a utilisation target, led mainly through technical leadership and project oversight. You will guide architecture decisions, assess delivery quality and help teams resolve complex challenges, without being the primary hands-on builder.

Key responsibilities

• Lead, coach and develop a team of technical architects across ANZ, set expectations, support career growth and give performance feedback.
• Act as a billable technical lead and delivery advisor, achieving a utilisation target through architecture guidance, technical reviews, project oversight and customer advisory.
• Own delivery of engagements by Snowflake architects and partners, working with customers and go-to-market teams to turn requirements into scoped engineering work and milestones.
• Guide customers and delivery teams through problem definition, design, development, evaluation, deployment and operational handover for AI agents and generative AI applications, including RAG and integration with enterprise tools.
• Build trusted customer relationships, coordinate stakeholders, manage expectations, raise risks early and act as the manager-level escalation owner.
• Coordinate team capacity and assignments, balancing customer commitments, billable delivery and time for coaching.
• Review solution designs and delivery quality, including grounding, security, governance, evaluation and observability, and guide teams in addressing technical debt.
• Partner with Product Management and Engineering on planning, dependencies and customer feedback.
• Travel to work with customers on site up to 25% of the time.

Required profile

• 8+ years of relevant experience preferred in customer-facing technical consulting, solution architecture or AI/ML delivery, with responsibility for leading complex enterprise engagements.
• Experience managing and developing technical professionals, including coaching and performance management.
• Accountability for customer outcomes across internal and partner teams, with stakeholder coordination and escalation resolution.
• Degree in computer science, engineering, mathematics or a related field, or equivalent experience.

Required skills

• Generative AI application development lifecycle, including use case framing, model selection, prompt and context design, agent orchestration, tool integration and evaluation.
• Production practices for LLM applications and AI agents, including evaluation, regression testing, deployment, observability, guardrails and human oversight, plus traditional ML and MLOps.
• Cloud architecture with at least one public cloud platform (AWS, Azure or Google Cloud).
• Practical Python, APIs and frameworks for building LLM applications and AI agents, with code-review judgement.

Bonus points: experience delivering generative AI on Snowflake, reusable architecture patterns, agent orchestration or retrieval/vector search tools, and industry expertise in financial services, retail or manufacturing.