We are looking for an AI Security Architect to help shape and strengthen the security posture of enterprise AI capabilities in Pennsylvania. This contract opportunity is ideal for a security specialist who can guide the safe adoption of AI platforms, agent-based tools, and AI-assisted development practices while aligning with internal standards and regulatory expectations. The role works closely with technology, risk, compliance, and business teams to evaluate emerging capabilities, address evolving threats, and support responsible innovation.<br><br>Responsibilities:<br>• Develop and refine security architecture for AI platforms, intelligent agents, and AI-assisted coding solutions to support secure deployment and ongoing operations.<br>• Assess platform enhancements, configuration updates, and newly introduced AI features to identify potential risk and recommend practical safeguards before implementation.<br>• Establish and improve protective controls for AI environments, including permissions, monitoring, logging, data safeguards, and usage restrictions.<br>• Analyze how sensitive and regulated information is handled within AI workflows, and support governance efforts related to classification, labeling, and responsible data use.<br>• Review connectors, plugins, integrations, and agent-driven capabilities to confirm appropriate access levels and reduce exposure across teams and systems.<br>• Conduct structured security evaluations of AI tools, models, and services to verify alignment with internal policies and relevant industry guidance.<br>• Research new AI security technologies and threat patterns, including prompt-based attacks, model misuse, and unintended data exposure, and identify opportunities for improvement.<br>• Partner with stakeholders across IT, risk, compliance, and business functions to communicate findings and advance secure AI adoption.<br>• Support secure software development by reviewing AI-generated code practices and incorporating AI-focused security checks into engineering workflows.<br>• Produce meaningful security metrics, including key risk and performance indicators, to strengthen monitoring and decision-making for AI security operations.
We are looking for a Snowflake Data Engineer to build modern data solutions that support analytics, AI, and enterprise decision-making. This role will focus on creating reliable pipelines, scalable data models, and secure data products within a Snowflake environment. The position is based in Radnor, Pennsylvania, and offers the opportunity to work closely with engineering, security, product, and business teams on high-impact initiatives.<br><br>Responsibilities:<br>• Architect and maintain scalable data pipelines, transformation workflows, and structured data models within Snowflake to support reporting, analytics, and AI use cases.<br>• Develop and deploy AI and machine learning capabilities using Snowflake-native tools, including intelligent agents, search-driven experiences, and customer-facing applications where applicable.<br>• Define and manage semantic views and business logic layers that provide governed, consistent definitions for analytics and AI consumption.<br>• Implement and support data ingestion frameworks using technologies such as Kafka, Snowpipe, APIs, Openflow, and third-party connectors, including integrations with enterprise platforms like NetSuite.<br>• Create reusable engineering utilities and automation with SQL, SnowSQL or related Snowflake tooling, Python, and JavaScript when appropriate.<br>• Establish strong production standards through automated testing, data quality validation, observability, exception handling, and controlled deployment processes.<br>• Tune queries, pipelines, AI workloads, and data structures to improve performance, scalability, maintainability, and downstream usability.<br>• Design secure data-sharing solutions and data-product delivery patterns for internal stakeholders, external partners, and customers.<br>• Collaborate with platform administrators and security teams to align access controls, governance requirements, identity integration, and production readiness for Snowflake solutions.<br>• Investigate and resolve issues affecting pipelines, semantic models, applications, and data quality while partnering across technical and business teams to deliver durable solutions.