Job Title: AI Architect
Job Summary:
The AI Architect is responsible for designing, developing, and overseeing the architecture of artificial intelligence solutions leveraging Palantir Foundry as a core enterprise data platform. This role works closely with stakeholders and technical teams to ensure scalable, secure, and effective AI implementation that aligns with business objectives and drives value from commercial data across Foundry.
Key Responsibilities:
Architect end-to-end AI solutions using Foundry, including machine learning models, large-scale data pipelines (PySpark), and production-grade deployment architectures within Foundry’s ecosystem.
Evaluate and select optimal ML and data technologies, frameworks, and platform components within Foundry and compatible cloud environments.
Establish best practices, governance, and architectural standards for AI and data science projects on Foundry, focusing on security, compliance, scalability, and maintainability.
Collaborate closely with data engineers, data scientists, software developers, and product managers to ensure seamless integration of commercial data sources and AI/analytics workflows in Foundry.
Oversee integration of AI models and analytic workflows into existing business systems—ensuring interoperability with Foundry APIs and data connectors.
Ensure security, data privacy, governance, and ethical considerations in all Foundry-based AI solutions.
Lead review and troubleshooting of system architecture, AI performance, reliability, and data pipeline health on Foundry.
Stay informed of AI, ML, data engineering, and Foundry platform advancements, championing adoption of innovative solutions.
Qualifications:
Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
Proven experience as an AI Architect, ML Engineer, or similar role implementing solutions on Foundry, PySpark, and cloud-based big data environments.
Deep understanding of AI/ML algorithms, model optimization, and enterprise-grade model deployment (preferably via Foundry).
Experience with cloud platforms (e.g., AWS, Azure, GCP), distributed data processing (PySpark), and ML tools/frameworks (e.g., MLlib, TensorFlow, PyTorch).
Strong knowledge of data engineering, security, compliance, and software architecture—especially within the Foundry platform ecosystem.
Excellent communication, problem-solving, and project management skills.
Preferred Qualifications:
Experience designing AI and advanced analytics on Foundry or similar big data platforms for pharma/commercial data applications.
Knowledge of MLOps, DevOps, CI/CD, and automated model pipelines within Foundry and cloud-based environments.
Familiarity with big data ecosystems (Foundry, Spark, Hadoop) and commercial data source integration.