Senior AI Engineer: Agentic Workflows & Production Systems

Tether; Rosario; Híbrido; ARS 185.448.000 - 278.173.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Professional growth

Competitive compensation

Exciting projects

Flextime

Descripción de la vacante

AgileEngine is seeking a Senior AI Engineer to design and build agentic workflows and AI-powered products for enterprise customers in higher education. The role requires 5+ years in software product development, strong Java/Spring Boot skills, and hands-on AI agent experience.

The candidate will lead architecture for tool-using LLMs, memory, and multi-agent collaboration, and will mentor teams while delivering production-ready systems across cloud-based environments.

Formación

• 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.

Responsabilidades

• 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 escalate 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.

Conocimientos

Java

Spring Boot

Relational databases

AI agents

tool-using LLMs

AWS

TypeScript

Python

RESTful APIs

distributed systems

testing

observability

security

scalability

leadership

Herramientas

AWS

REST APIs

Descripción del empleo

AgileEngine is seeking a Senior AI Engineer to design and build agentic workflows and AI-powered products for enterprise customers in higher education. The role requires 5+ years in software product development, strong Java/Spring Boot skills, and hands-on AI agent experience.

The candidate will lead architecture for tool-using LLMs, memory, and multi-agent collaboration, and will mentor teams while delivering production-ready systems across cloud-based environments.