Principal Software Engineer - CoreAI

Leads by example and mentors' others to produce extensible and maintainable code used across the company. Leverages deep subject-matter expertise of cross-product features with appropriate stakeholders (e.g., project managers) to lead multiple product's project plans, release plans, and work items. Own and define end-to-end data and analytics architecture for CoreAI and Foundry platforms, setting long-term technical direction for scalable, reliable, and cost-effective analytics supporting AI workloads. Design, build, and optimize large-scale, robust data pipelines and architectures that support CoreAI's analytics initiatives. Data Governance & Trust: follow best practices for data quality, lineage, security, and compliance. Collaborate with stakeholders to define trustworthy data sets and implement rigorous data validation protocols, ensuring CoreAI's analytics are both accurate and auditable. Analytics Enablement: Partner with data scientists, analysts, and business leaders to translate business needs into technical solutions. Enable self-service analytics and empower teams by building data models, semantic layers, and tools that streamline access to trusted information. Cross-Functional Collaboration: Work closely with product managers, software engineers, AI researchers, and business stakeholders to align data solutions with business goals. Contribute actively to the infrastructure and culture needed to scale quantity and quality of data insights across CoreAI. Mentor other software engineers, engineers, and PMs. Leverage AI to accelerate workflows and amplify team productivity. Bachelor's Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience. These requirements include, but are not limited to the following specialized security screenings: 5+ years of experience leading software engineering and analytics projects that delivered measurable product and growth wins. Deep experience architecting and operating large scale data pipelines in cloud environment, preferably Azure. Ability to write clean, working code using core algorithms, data structures, and analytics‑oriented problem‑solving. Understanding of data governance, privacy, lineage, and security best practices, especially within highly regulated or enterprise environments. Excellent communication skills to convey complex technical concepts to both technical and non-technical audiences. Experience using AI tools in software engineering, data science, and analytics workflows. Experience both prototyping and deploying data products.