* Salário: R$ 3.000 a R$ 6.000 por mês (estimado)
* O valor exibido é uma estimativa calculada com base em dados públicos e referências do mercado. Não garantimos que este seja o salário oferecido para esta vaga específica.
Área: Tecnologia da Informação
Nível: Junior
Please submit your resume in English - we can only consider applications submitted in this language.
Minimum qualifications:
- Bachelor’s degree in Engineering, Computer Science, a related field, or equivalent practical experience.
- 6 years of experience building and shipping production-grade AI-driven solutions to external or internal customers using Python, Typescript or comparable languages.
- Experience leading technical discovery sessions with business stakeholders and engineering teams to define AI and hardware infrastructure requirements.
- Experience designing and building AI systems on cloud platforms (e.g., Confidencial (Apenas para Cadastrados) Cloud Platform (GCP)).
- Experience building pipelines for structured, unstructured data, incorporating vector databases and retrieval-augmented generation (RAG)-like architectures to power enterprise-grade AI solutions.
Preferred qualifications:
- Master’s degree or PhD in AI, Computer Science, or a related technical field.
- Experience implementing multi-agent systems using frameworks (e.g., LangGraph, CrewAI, or Confidencial (Apenas para Cadastrados)’s Agent Development Kit (ADK)) and patterns like ReAct, self-reflection, and hierarchical delegation.
- Knowledge of large language models (LLM) native metrics (tokens/sec, cost-per-request) and techniques for optimizing state management and granular tracing.
About the job
As a GenAI Forward Deployed Engineer at Confidencial (Apenas para Cadastrados) Cloud, you will be an embedded builder bridging the gap between frontier AI products and production-grade reality for our customers. You will function as a builder-consultant, moving beyond high-level architecture to code, debug, and jointly ship bespoke agentic solutions directly within the customer’s environment.In this role, you will manage blockers to production including solving the integration complexities, data readiness issues, and state-management issues that prevent AI from reaching enterprise-grade maturity. By embedding with accounts, you will serve a dual purpose: providing white-glove deployment of AI systems and acting as a critical feedback loop, transforming real-world field insights into Confidencial (Apenas para Cadastrados) Cloud’s future product roadmap.It's an exciting time to join Confidencial (Apenas para Cadastrados) Cloud’s Go-To-Market team, leading the AI revolution for businesses worldwide. You’ll excel by leveraging Confidencial (Apenas para Cadastrados)'s brand credibility—a legacy built on inventing foundational technologies and proven at scale. We’ll provide you with the world's most advanced AI portfolio, including frontier Gemini models, and the complete Vertex AI platform, helping you to solve business problems. We’re a collaborative culture providing direct access to DeepMind's engineering and research minds, empowering you to solve customer challenges. Join us to be the catalyst for our mission, drive customer success, and define the new cloud era—the market is yours.
Responsibilities
- Serve as the lead developer for AI applications, transitioning from rapid prototypes to production-grade agentic workflows (e.g., multi-agent systems, model context protocol server (MCP) servers) that drive measurable return on investment.
- Architect and code the connective tissue between Confidencial (Apenas para Cadastrados)’s AI products and customer's live infrastructure, including APIs, legacy data silos, and security perimeters.
- Build high-performance evaluation pipelines and observability frameworks to ensure agentic systems meet rigorous requirements for accuracy, safety, and latency.
- Identify repeatable field patterns and technical friction points in Confidencial (Apenas para Cadastrados)’s AI stack, converting them into reusable modules or product feature requests for the Engineering teams.
- Drive engineering excellence by mentoring talent, co-building with customer teams, and influencing cross-functional strategies to uplevel organizational technical capabilities.