About Cornerstone: Cornerstone powers the future-ready workforce with modern, AI-driven employment solutions. Our platform enables companies to develop, manage, and engage their talent—unlocking growth and innovation across organizations of all sizes. Who We’re Looking For: Cornerstone is seeking a visionary and highly accomplished Distinguished Principal AI Engineer to spearhead the creation of groundbreaking AI and machine learning solutions across our industry-leading workforce agility - Galaxy ecosystem. This is a rare opportunity for a true innovator—someone who thrives on architecting and hands-on building intelligent, autonomous systems at massive scale. You’ll be driving the future of workforce technology by delivering AI-powered applications that are robust, secure, ethical, and brilliantly performant. In this role you will… Advanced Architecture System Design: Architect, implement, and scale modern, distributed AI systems—including training pipelines, streaming data processing, serverless microservices, and MLOps infrastructure—to deliver enterprise-grade reliability and security. Lead end-to-end technical delivery of AI Native Products —owning E2E architecture/design and hands-on engineering excellence from design through deployment, scaling, and continuous improvement. Lead E2E architecture for AI native SaaS Products —distributed systems, APIs, integrations, security, and reliability. Drive hands-on software engineering across the full lifecycle (design, build, deploy, optimize) with strong engineering fundamentals. Architect and scale modern distributed architectures (serverless/microservices, Kubernetes, Docker) and data/compute workflows. Build production-grade AI/ML capabilities (LLMs/GenAI, NLP, recommenders) with MLOps-grade reliability and monitoring. Design end-to-end streaming + batch data pipelines (ETL, Spark, data lakes) and scalable inference patterns- Deliver agentic/LLM workflows (orchestration, tools, vector search, knowledge graphs) with robust integration to enterprise systems. Set standards for AI safety, fairness, explainability, privacy, and compliance. Own CI/CD, DevSecOps, and GitOps practices to ensure secure, repeatable, enterprise deployments. Mentor teams through architecture reviews, best practices, and engineering excellence—driving responsible engineering across SDLC. You’ve got what it takes if you have… 12+ years of software engineering with proven ownership in product engineering, architecture operational excellence. Deep expertise in engineering fundamentals (system design, distributed systems, data/compute architecture, scalability, security). Strong hands-on experience leading complex architecture and delivery for enterprise platforms. Proven experience with cloud (AWS/Azure/GCP), Kubernetes/Docker, and modern API/service design. Strong background in ML/LLM/GenAI systems delivery or architecting AI-enabled solutions with production-grade MLOps practices. Experience with CI/CD, GitOps, DevSecOps, and enterprise security practices- Strong understanding of responsible AI (privacy, bias, explainability) and real-world deployment constraints. HR tech/SaaS/enterprise domain experience is a plus. #LI-Onsite