We’re excited about you if you have:
The Builder Mindset - Strong technical foundation in data science. Comfortable working directly with code, APIs, notebooks, development frameworks, and enterprise architectures.
Hands-On AI Experience - Practical experience building or supporting AI applications across machine learning, deep learning, computer vision, time-series analytics, predictive modeling, anomaly detection, and generative AI. Comfortable discussing model architectures, training and evaluation methodologies, inference patterns, and production deployment considerations across a broad range of enterprise AI workloads.
Enterprise Discovery and Solutioning Experience - Proven success in technical pre-sales, solution architecture, consulting, customer engineering, or similar roles involving the discovery, qualification, and design of complex enterprise technology initiatives.
Data Readiness Assessment Skills - Ability to evaluate data quality, governance, security, compliance, operational readiness, and infrastructure constraints that impact successful private AI deployments.
Executive Communication Skills - Exceptional ability to engage technical and executive audiences, facilitating conversations that connect business outcomes with practical implementation strategies.
Technical Proficiency - Experience with Python, APIs, cloud-native architectures, data pipelines, MLOps, and modern AI development ecosystems.