Senior Architect (Data, Cloud, AI)

About Ellucian

Ellucian powers innovation for higher education, partnering with approximately 3,000 customers across 50 countries, serving more than 21 million students. Ellucian's AI-powered platform, trained on the richest dataset available in higher education, drives efficiency, personalized experiences, and strengthened engagement for all students, faculty and staff. Fueled by decades of experience with a singular focus on the unique needs of learning institutions, the Ellucian platform features best-in-class SaaS capabilities and delivers insights needed now and into the future. These solutions and services span the entire student lifecycle, including data-rich tools for student recruitment, enrollment, and retention to workforce analytics, fundraising, and alumni engagement. Ellucian's innovative solutions, vast ecosystem of partners and user community of more than 45,000 provides best practices leading to greater institutional success and achieving better student outcomes.

About the Opportunity

Ellucian is seeking a highly skilled and innovative Senior Architect to lead the architecture and technical strategy for our next-generation Data Platform and analytics solution. This role will be instrumental in transforming our current data warehouse ecosystem into a modern, scalable, cloud-native Lakehouse platform capable of supporting analytics, AI/ML workloads, agentic AI experiences, and real-time data products.

This is a hands-on architecture leadership role requiring deep expertise in data platforms, data warehouse, distributed systems, cloud technologies, and emerging AI technologies.

As a key technical leader , role offers opportunities to spearhead technical initiatives, mentor engineers at all levels, and work closely with internal product managers, experienced engineers, and cross-functional teams to design, develop, test, and deliver advanced features that enhance student success and drive higher education transformation.

Where You Will Make an Impact

Architecture & Strategy

• Build and own the target-state architecture for a next-generation Lakehouse platform.
• Develop technology roadmaps aligned with business strategy and product vision.
• Lead architectural decisions across data ingestion, storage, processing, governance, observability, security, and AI enablement.
• Establish architecture principles, standards, and reference architectures.

Platform Modernization

• Lead migration from traditional data warehouse architectures to modern Lakehouse architectures.
• Design scalable data platforms supporting structured, semi-structured, and unstructured data.
• Evaluate and drive adoption of technologies such as Apache Iceberg, Delta Lake, Apache Spark, DuckDB, Trino, Flink, Kafka, and cloud-native analytics services.
• Design multi-tenant SaaS architectures with strong security and data isolation.

AI & Intelligent Data Platform

• Define architecture patterns enabling AI-powered data experiences.
• Design platforms supporting:
• Generative AI applications
• Agentic AI workflows
• Retrieval-Augmented Generation (RAG)
• Vector databases and semantic search
• AI-assisted analytics and insights

• Partner with AI teams to operationalize ML and GenAI workloads.
• Evaluate emerging AI technologies and determine applicability to the platform roadmap.

Technical Leadership

• Take ownership of critical tasks from specification review through final testing and deployment, ensuring timely and high-quality delivery.
• Serve as the highest level technical authority for the platform.
• Mentor architects and senior engineers.
• Conduct architecture reviews and guide critical design decisions.
• Drive engineering excellence and technical innovation across teams.

Scalability, Reliability & Operations

• Architect for high availability, performance, resiliency, and cost optimization.
• Define observability and operational excellence standards.
• Drive platform reliability through automation and SRE practices.
• Establish governance around performance, security, compliance, and data quality.

What You Will Bring

• Experience: Bachelor / Master's degree in Computer Science, Data Engineering, AI, or related field. Overall 15+ years of software engineering exp with 7+ years of professional software development experience in a product or SaaS environment building modern Data platform.
• Deep expertise in modern data architectures including Data warehouse, Data Mesh, Data platforms.
• Deep expertise in distributed data processing frameworks, Apache Spark, Trino, Flink, Kafka.
• Experience with open table formats, Apache Iceberg, Delta Lake.

• Strong understanding of Metadata management, Lineage, observability.
• Distributed Systems: Experience designing, building, and evolving large-scale distributed systems, microservices, event-driven architectures, and highly available production services.
• Cloud and Platform Engineering: Strong knowledge of cloud platforms such as AWS, containerization, infrastructure automation, and modern operational practices for reliability, scalability, and cost efficiency.
• Engineering Excellence: Deep experience with CI/CD, code review, test automation, observability, release engineering, and DevOps practices in modern software delivery environments.
• Security and Risk Awareness: Strong understanding of authentication, authorization, encryption, secure design, and practical application security principles in enterprise software.
• LLM and Agentic Systems Experience: Demonstrated experience building or guiding solutions that use large language models, including agent-based workflows, prompt and context design, tool orchestration, structured outputs, and human-in-the-loop validation patterns.
• Model Selection and Evaluation: Experience working with multiple LLMs or AI providers and making practical tradeoff decisions across model quality, latency, cost, reliability, safety, and enterprise suitability.
• AI Engineering Practices: Understanding of core patterns for production AI systems such as retrieval-augmented generation, evaluation frameworks, observability, prompt management, guardrails, fallback strategies, and secure handling of sensitive data.
• Judgment and Governance: Ability to evaluate AI-generated output critically, define validation standards, identify risk areas, and maintain human accountability for technical decisions and delivered outcomes.
• Technical Communication: Excellent communication, collaboration, and organizational skills, with the ability to align engineers, product partners, and stakeholders around technical direction and execution tradeoffs.
• Mentorship and Influence: Proven experience mentoring engineers, leading technical discussions, raising engineering standards, and shaping development practices across a team or organization.

What makes #Ellucianlife

• 12 days vacation, 10 days causal leaves plus 11 public holidays

• Competitive gratuity policy
• Group insurance and Annual health checkup plan with a variety of family and wellness benefits.
• Thrive Flex Lifestyle Account (LSA) that allows you to contribute towards your health,

financial or learning interests

• 5 charitable days to support the community that supports us
• Wellness

o Headspace (mental health) o Wellbeats (virtual fitness classes)

• RethinkCare – caregiver support
• Diversity and inclusion programs that promote employee resource groups such as: Buzzinga and Lean In Team to name a few.
• Parental leave
• Employee referral bonuses to encourage the addition of great new people to the team
• We Foster a learning culture with:• Education Assistance Program
• Professional development opportunities
• LinkedIn Learning

#LI-SN1

#LI-Hybrid