Lead Software Engineer - Multiple Teams

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 Lead Software Engineer to join various teams focused on developing new cloud-based, SaaS higher education solutions. This hands-on role involves full-stack development, technical leadership, and collaboration within agile environments to deliver scalable, secure, and high-quality products. As a Lead Software Engineer, you will take on pivotal roles in driving complex and impactful projects, leveraging cutting-edge technologies and leading the full software development lifecycle. This 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

• Technical Leadership and Delivery: Lead the design, development, delivery, and maintenance of complex SaaS solutions and large ERP systems, providing technical direction and accountability for high-quality outcomes
• Full-Stack Engineering: Engage in full-stack development, including advanced front-end frameworks (e.g., React, HTML5, TypeScript) and robust back-end APIs using languages such as JavaScript/TypeScript (Node.js), and Python. Experience with C# or Java is a plus.
• Strategic Planning: Collaborate with product leadership to define technical strategies and roadmaps. Ensure alignment with business goals and objectives.
• Quality Assurance: Advocate and implement best practices in agile software development, continuous integration/delivery (CI/CD), and DevOps processes. Ensure high-quality, scalable code, unit and functional tests, and comprehensive developer documentation (API docs, usage notes).
• Collaboration: Work closely with product managers, analysts, and team members to clarify complex requirements and ensure robust, future-proof designs. Facilitate cross-functional collaboration to drive project success.
• AI Platform and Agentic Engineering: Lead the design and implementation of AI-enabled engineering solutions, including LLM-backed workflows, agentic systems, tool-calling patterns, and model evaluation approaches that improve developer productivity, product capabilities, and operational efficiency.
• Engineering Context and Standards: Create and maintain the architectural guidance, coding patterns, domain context, review criteria, and team conventions needed for engineers and AI tools to produce consistent, maintainable outcomes.
• Ownership and Accountability: Take ownership of critical tasks from specification review through final testing and deployment, ensuring timely and high-quality delivery. Manage project timelines and deliverables.
• Problem Solving and System Analysis: Lead investigation of complex functional, integration, scalability, reliability, and performance issues through research, proof of concept, data analysis, and pragmatic technical decision-making.
• Platform and Tooling Solutions: Design, develop, test, and deliver new platform and tooling solutions using modern technologies and microservices architecture.
• Team Development: Mentor engineers at all levels through design reviews, code reviews, technical coaching, and practical guidance on engineering quality, AI-assisted development, and sound decision-making.
• Continuous Improvement: Drive adoption of better tools, practices, and technologies that improve product quality, operational efficiency, customer experience, and team effectiveness.

What you will bring

• Experience: 7+ years building software in a product or SaaS environment.
• Programming Languages: Fluency across several languages. Node.js, JavaScript and TypeScript with React.js, Python, and related frameworks.
• System Design: Proven ability to turn an ambiguous requirement into a coherent design. Service boundaries, data models, API and event contracts, failure modes, capacity, cost. Clear articulation of tradeoffs. Reviews and challenges designs from other engineers.
• Large-Scale Production Systems: Experience running high-availability services at scale. Evolving systems under load, migrating without downtime, diagnosing failures across service boundaries, owning reliability and cost outcomes.
• Cloud and Platform Engineering: Depth in AWS or comparable platforms. Containers, infrastructure automation, and operational practice for reliability, scalability, and cost efficiency.
• Engineering Excellence: Depth in CI/CD, code review, test automation, observability, release engineering, and DevOps practice.
• Security and Risk Awareness: Strong grasp of authentication, authorization, encryption, secure design, and applied security for enterprise software.
• Agentic SDLC: building software with agents: Experience delivering software through an agent-assisted lifecycle. Directs several specialised agents across spec, design, build, test, and review. Knows where human expertise stays mandatory. Treats agent output as evidence to verify, not work to accept.
• AI Agent Engineering: building agents into the product: Experience designing and shipping agent capabilities inside a product. Agent architecture, tool interfaces, prompt and context design, memory and state, structured outputs, retrieval, guardrails, human-in-the-loop validation. Operates these systems in production with evaluation, observability, and secure data handling.
• Model Selection and Evaluation: Working knowledge of current models across providers. Matches a model to a task on quality, latency, cost, reliability, and enterprise fit. Applies this judgment twice, to the agents building the software and to the agents shipping inside the product. Decides with evidence, not benchmark headlines. Keeps this knowledge current.
• Judgment and Governance: Critical evaluation of AI output. Defines validation standards, names risk areas, and holds human accountability for technical decisions and delivered outcomes.
• Technical Communication: Clear communication and organization. Aligns engineers, product partners, and stakeholders around technical direction and execution tradeoffs.
• Mentorship and Influence: Mentors engineers, leads technical discussions, raises engineering standards, and shapes development practice across a team or organization.

What makes #Ellucianlife