Senior Agentic AI Engineer

AgileEngine, LLC.; Brasil; A distancia; BRL 240.000 - 420.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Growth without limits: build your技能

Descripción de la vacante

AgileEngine, LLC in Brazil is seeking a Senior AI Engineer to design agentic workflows and AI-powered products for enterprise customers in higher education.

The role requires hands-on AI development with Python, TypeScript, AWS, Java/Spring Boot, React, and strong English communication. You will lead production-grade systems, mentor engineers, and drive scalable, secure AI solutions across teams.

Formación

• 5+ years of experience in a software product development environment.
• Strong proficiency with Java and Spring Boot.
• Experience with JavaScript and React.
• 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.
• Upper-intermediate English level.

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 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.

Conocimientos

Python

TypeScript

AWS

Java

Spring Boot

JavaScript

React

English communication

Herramientas

Java

Spring Boot

JavaScript

React

Python

TypeScript

RESTful APIs

AWS

Descripción del empleo

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.

The mandatory requirements are hands‑on experience building AI applications and agents, Python, TypeScript, and AWS, 5+ years in software product development, Java and Spring Boot, JavaScript and React, relational databases, and strong English communication skills.

Must haves

• 5+ years of experience in a software product development environment.
• Strong proficiency with Java and Spring Boot.
• Experience with JavaScript and React.
• 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.
• Upper‑intermediate English level.

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

• Growth without limits: build your skills through mentorship, internal TechTalks, challenging projects, and a dedicated annual learning budget
• Competitive compensation: get recognition that reflects your skills and impact, with regular performance and compensation reviews
• Flexibility: work 100% remotely with flexible hours that support focus, autonomy, and a healthy work rhythm
• Meaningful, modern projects: build impactful products using modern technologies alongside global teams and leading brands
• Collaborative culture: join a supportive environment with zero micromanagement where ideas are welcomed and contributions are recognized
• Well-being & support: access local well-being programs and people-focused support tailored to your location