Senior Agentic AI Engineer ID98909

AgileEngine

Madrid

Hybrid

EUR 70,000 - 110,000

Full time

3 days ago
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Benefits offered by this job

Professional growth
Competitive compensation
Exciting projects
Flextime

Job summary

AgileEngine is seeking a Senior AI Engineer to design and build agentic workflows and AI-powered products for enterprise customers in higher education. You will lead the development of scalable, observable systems and mentor engineers in an agentic-first approach.

You will work across product and engineering teams to turn opportunities into reliable technical solutions, implement robust tests, and ensure security and governance. Remote-friendly with flex-time and office options.

Qualifications

  • 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.

Responsibilities

  • 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 agentic development.
  • Mentor engineers and help shape an agentic-first technical strategy across the organization.
  • Collaborate with product and engineering leaders to connect agentic capabilities to meaningful outcomes.
  • Demonstrate the ability to use AI coding agents as productive engineering collaborators across an application codebase.
  • Provide agents with clear context, constraints, architecture, acceptance criteria, and technical direction.
  • Review, test, secure, and improve agent-generated code rather than accepting outputs without verification.
  • Decompose complex application work into agent-ready tasks while maintaining architectural consistency and product intent.
  • Create workflows where agents can reason, select tools, call APIs, manage state, recover from failures, and elevate to people when appropriate.
  • Design agentic applications around real user needs, including intuitive experiences, reliable workflows, permissions, audit trails, and meaningful error handling.
  • Move from prototype to production by addressing performance, scalability, security, monitoring, evaluation, cost, and ongoing maintenance.
  • Understand problems deeply, make appropriate tradeoffs, and deliver complete solutions that customers can depend on.

Skills

Leadership
Strategic thinking
Mentoring
Communication
Problem solving

Tools

Java
Spring Boot
TypeScript
Python
RESTful APIs
AWS
Agentic workflows

Job description

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 agentic development.
  • Mentor engineers and help shape an agentic-first technical strategy across the organization.
  • Collaborate with product and engineering leaders to connect agentic capabilities to meaningful outcomes.
  • Demonstrate the ability to use AI coding agents as productive engineering collaborators across an application codebase.
  • Provide agents with clear context, constraints, architecture, acceptance criteria, and technical direction.
  • Review, test, secure, and improve agent-generated code rather than accepting outputs without verification.
  • Decompose complex application work into agent-ready tasks while maintaining architectural consistency and product intent.
  • Create workflows in which agents can reason, select tools, call APIs, manage state, recover from failures, and elevate to people when appropriate.
  • Design agentic applications around real user needs, including intuitive experiences, reliable workflows, permissions, audit trails, and meaningful error handling.
  • Move from prototype to production by addressing performance, scalability, security, monitoring, evaluation, cost, and ongoing maintenance.
  • Understand problems deeply, make appropriate tradeoffs, and deliver complete solutions that customers can depend on.
PERKS AND BENEFITS
  • Professional growth: Mentorship, TechTalks, and personalized growth roadmaps.
  • Competitive compensation: USD-based pay with education, fitness, and team activity budgets.
  • Exciting projects: Modern solutions with Fortune 500 and top product companies.
  • Flextime: Flexible schedule with remote and office options.
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