Senior AI Agentic Engineer (Remote)

Hire Hangar, Inc.; Rosario; Hybrid; ARS 231,811,000 - 324,535,000; Full time

Benefits offered by this job

Professional growth

Competitive USD-based pay

Exciting projects

Flextime

Job summary

AgileEngine seeks a Senior AI Engineer to design and build agentic workflows and AI-powered products for enterprise customers, including higher education. You will lead the development of agent orchestration, tool usage, context management, and multi-agent collaboration on AWS.

You will guide planning, testing, deployment, and production delivery, with a strong focus on reliability, security, and observability. Remote-friendly with strong collaboration across teams.

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 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.

Skills

Java

Spring Boot

Relational databases

AI agents

Tool-using LLM apps

Agent orchestration

AWS

RESTful APIs

TypeScript

Python

Distributed systems

Leadership

Testing & observability

Security & governance

Job description

AgileEngine seeks a Senior AI Engineer to design and build agentic workflows and AI-powered products for enterprise customers, including higher education. You will lead the development of agent orchestration, tool usage, context management, and multi-agent collaboration on AWS.

You will guide planning, testing, deployment, and production delivery, with a strong focus on reliability, security, and observability. Remote-friendly with strong collaboration across teams.