AgileEngine is an Inc. 5000 company that creates award-winning software for Fortune 500 brands and trailblazing startups across 17+ industries. We rank among the leaders in areas like application development and AI/ML, and our people-first culture has earned us multiple Best Place to Work awards.

Why join us

If you're looking for a place to grow, make an impact, and work with people who care, we'd love to meet you

About the role

We are looking for a Senior AI Engineer to design and build agentic workflows and AI-powered products for enterprise customers in higher education.

MUST HAVES

- 5+ years of experience in a software product development environment.
- Strong proficiency with Java and Spring Boot.
- Experience with relational databases.
- Hands-on experience building AI agents, tool-using LLM applications, or orchestrated workflows.
- Experience using agents to support coding, code review, testing, release management, or incident response.
- Senior-level experience building and operating production software systems.
- Experience with TypeScript, Python, RESTful APIs, and infrastructure on AWS.
- Experience with APIs, workflow engines, event-driven architectures, integrations, or distributed systems.
- Strong understanding of testing, observability, security, permissions, and failure recovery.
- Ability to turn ambiguous opportunities into practical, reliable technical solutions.




- Strong communication skills and the ability to influence engineering practices across a team.
- Experience building enterprise SaaS or multi-tenant systems.
- Leadership mindset and ability to drive changes across different teams.

NICE TO HAVES

- Experience with multi-agent systems, RAG, vector search, agent evaluation, or human-in-the-loop workflows.
- Familiarity with higher education technology and its privacy and compliance requirements.
- Experience leading technical transformation or introducing new engineering practices.

WHAT YOU WILL DO

- Design and build agentic workflows that coordinate tools, services, data, and human approvals.
- Develop reusable patterns for agent orchestration, tool use, context management, memory, and multi-agent collaboration.
- Use agentic coding tools throughout the development lifecycle, including planning, implementation, testing, debugging, refactoring, code review, and documentation.
- Integrate agents into software development, testing, deployment, support, and operational workflows.
- Establish standards for agent evaluation, observability, reliability, security, and governance.
- Prototype new agentic capabilities and turn successful experiments into production systems.
- Build complete, usable products—not just demonstrations or isolated model integrations.
- Identify opportunities to improve engineering productivity and product delivery through agent

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