Senior AI Backend Architect — Agentic Workflows, Remote

World-Business-Lenders,-Ll

Ciudad de Mendoza

In loco

ARS 185.448.000 - 262.719.000

Tempo pieno

3 giorni fa
Candidati tra i primi

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Vantaggi offerti da questo lavoro

Professional growth
Competitive compensation
Exciting projects
Flextime

Descrizione del lavoro

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 agent orchestration patterns and integrate agents across development, testing, deployment, and operations.

The role emphasizes scalable, secure, production-grade systems, with leadership and collaboration across teams to deliver reliable AI-driven solutions. Hybrid/remote-friendly environment offered.

Competenze

  • 5+ years 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 apps, 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 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.

Mansioni

  • 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.

Conoscenze

Java
Spring Boot
RESTful APIs
TypeScript
Python
AWS
Agentic workflows
AI agents
Leadership
Communication
Enterprise SaaS
Multi-tenant systems

Strumenti

LLM tools
Workflow engines
APIs integration

Descrizione del lavoro

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 agent orchestration patterns and integrate agents across development, testing, deployment, and operations.

The role emphasizes scalable, secure, production-grade systems, with leadership and collaboration across teams to deliver reliable AI-driven solutions. Hybrid/remote-friendly environment offered.

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