Solutions Engineer (AI)

TL;DR

Solutions Engineer (AI/Data Cloud): Designing and implementing modern data and AI solutions for enterprise customers with an accent on technical pre-sales, solution architecture, and customer value realization. Focus on bridging business challenges with technical execution using SQL, Python, and the Snowflake AI Data Cloud.

Location: Melbourne or Sydney, Australia

Company

A cloud-native data platform powering the era of the agentic enterprise.

What you will do

• Drive the technical win across the sales cycle by partnering with account executives and cross-functional teams.
• Conduct discovery sessions, demonstrations, workshops, and proof-of-concept (POC) engagements.
• Guide customers on modern data architecture, solution design, and implementation across analytics, data engineering, and AI/ML.
• Translate complex business challenges into practical solution patterns that drive adoption and long-term value.
• Build trusted relationships with architects, engineers, and business stakeholders within strategic accounts.
• Collaborate with Product Management and Engineering to improve products, messaging, and field effectiveness.

Requirements

• Experience in solutions engineering, sales engineering, or technical pre-sales roles.
• Strong hands-on technical capability, including SQL and Python.
• Deep competency across modern data stacks (ETL/ELT, data warehouses, data lakes, and cloud-native platforms).
• Experience working with enterprise customers in complex technical and stakeholder environments.
• Excellent communication and presentation skills for both technical and executive audiences.

Nice to have

• Experience with AI and machine learning deployment workflows.
• Experience with cloud platforms such as AWS, Azure, or Google Cloud.
• Familiarity with BI tools like Tableau or Power BI.
• Background in enterprise SaaS and complex technical sales cycles.
• Degree in computer science, engineering, mathematics, or equivalent practical experience.

Culture & Benefits

• Opportunity to work in a fast-growing, innovative AI-native environment.
• Culture of low-ego individuals moving with an experimental mindset.
• Focus on redefining the future of work using AI as a high-trust collaborator.
• Dynamic and fast-moving environment emphasizing rapid testing of emerging capabilities.