What you will do

• Build strong, meaningful relationships with our customers and proactively seek to understand their technical and business objectives
• Drive technical engagement and adoption across the complete customer journey
• Champion customer needs internally, advocating for them within Robust Intelligence and leveraging your customer knowledge to influence the product roadmap
• Coordinate across multiple Robust Intelligence teams, including Product, Engineering, Sales, and Support to advance adoption, expansion, and other Customer Success priorities
• Become a power user of the RI platform: deeply understand the user experience (using the APIs, navigating the GUI, integrating with different platforms, etc.)
• Create and deliver tailored product demonstrations that address technical pain and show business value
• Design high-quality, differentiated proofs of concept that establish the value of the Robust Intelligence platform
• Scope customer engagements; investigate and understand customer needs
• Build bespoke machine learning validation solutions using the RI platform
• Work with customers to architect integrations with their existing machine learning stack
• Work with customers to design best practices, processes, and frameworks for their organization
• Gather, understand, and communicate customer feedback to RI’s Product and Engineering teams
• Own customer-facing technical communications to ensure a professional and concise message

What you bring to the team

• At least five years of professional experience as a sales engineer, customer architect, consulting, or other customer-facing technical field
• Strong knowledge of customer success and sales processes
• Knowledge of Python (or other programming languages)
• Strong experience with major public cloud platforms (e.g. AWS, Google Cloud Platform, Azure)
• Knowledge of Unix, Docker, Kubernetes, Python, REST
• Significant experience developing and delivering product demonstrations and leading proofs of concept
• Ability to establish trust at the CxO level as well as with technology practitioners
• Self-motivated and excited to work at a startup; comfortable with ambiguity, eager to learn, and able to thrive with little to no direct, daily oversight
• Strong communication skills (business fluency in spoken and written English)
• Ability to travel about 25% of the time to meet with your accounts

Nice to have

• Expertise in AI, ML, data science, or related spaces; general knowledge of statistics and applied ML
• Familiarity with the artificial intelligence ecosystem; familiarity with how data scientists and machine learning engineers develop and deploy AI models
• Experience building ML models and with ML pipelines
• Familiarity with different cloud platforms and their ML products (AWS Sagemaker, GCP Vertex AI, etc.)
• Familiarity with tooling and platforms in the ML ecosystem (Huggingface, MLFlow, Databricks, DataRobot, etc.)
• Bachelor’s degree (or equivalent) in computer science, engineering, mathematics, statistics, or another quantitative field