Arquiteto de Soluções de IA/ML

This is a fully remote position, open to applicants in Brazil.

📋 Description

• Understanding the context and challenges faced by the customer

• Collaborate with the sales team and stakeholders to grasp the context, needs, and challenges of clients

• Engage in discussions, data gathering, and alignment meetings to ensure clear understanding of the problem before suggesting any solution

• Question requests when necessary, aiming to delve deeper than the initial ask to uncover the true need

• Analysis and structuring of solutions

• Translate business problems into feasible digital solutions

• Structure workflows, business rules, and expected system behaviors

• Evaluate different approaches to solve the problem, considering impact, effort, and technical feasibility

• Ensure that the proposed solution makes sense for both the client and the development team

• Construction and detailing of scope

• Organize and structure requirements clearly and understandably for the technical team

• Write user stories, acceptance criteria, and business rules

• Ensure that the scope is complete, consistent, and aligned with the solution's objective

• Monitoring and validation of deliveries

• Oversee the development of solutions alongside the technical team

• Clarify doubts and adjust directions throughout execution

• Validate deliveries to ensure adherence to the problem and the defined solution

• Connection between areas

• Serve as a bridge between the client, sales, and technical teams

• Ensure alignment of expectations among all involved parties

• Communicate decisions, changes, and impacts clearly

⛳️ Requirements

• Knowledge of PyTorch and/or TensorFlow

• Proficiency in Python

• Solid understanding of high-level system architecture: REST APIs, system integrations, webhooks, authentication (OAuth, JWT), and data flows between applications

• Familiarity with relational databases and the ability to read and write basic to intermediate SQL queries for rule validation and data analysis

• Understanding of UX/UI concepts to collaborate with designers in creating user-centered solutions

• Ability to interpret technical diagrams (flowcharts, BPMN, sequence diagrams, ER) and create them when necessary

• Basic knowledge of programming languages and modern frameworks (coding is not required, but it aids communication with the technical team)

• Conceptual understanding of cloud architectures (AWS, Azure, or GCP)

• Experience with integrations involving ERPs, CRMs, or legacy systems

• Awareness of LGPD and best security practices applied to digital products

• Familiarity with analytics and product discovery tools (Hotjar, Mixpanel, Amplitude, Google Analytics)

• Experience with Postman or Insomnia for API exploration

• Utilization of AI tools in the workflow (Claude, ChatGPT, Cursor) to expedite documentation and analysis

• Knowledge in Artificial Intelligence

• Proficient use of generative AI assistants (Claude, ChatGPT, Gemini) to accelerate documentation, requirement analysis, user story writing, and workflow structuring

• Ability to create effective prompts (prompt engineering) to achieve consistent results in discovery, analysis, and documentation tasks

• Conceptual understanding of LLMs (Large Language Models): what they are, their purposes, limitations (hallucinations, context, cost), and when it makes sense to apply them in a solution

• Understanding of RAG (Retrieval-Augmented Generation) and document indexing for building solutions that combine AI with customer knowledge bases

• Experience in projects involving AI-based functionalities (chatbots, assistants, automatic classification, document data extraction, summarization, semantic search)

• Familiarity with APIs from AI providers (Anthropic, OpenAI, Azure OpenAI, AWS Bedrock) and their token pricing models

• Knowledge of AI agent orchestration (frameworks like LangChain, n8n with AI nodes, or similar) at a conceptual level

• Understanding of evaluating AI solutions: how to measure quality, define acceptance criteria, and structure tests for probabilistic functionalities

• Sensitivity to ethical and governance issues in AI: data privacy, bias, transparency, and compliance with LGPD in solutions processing client data

• Ability to identify automation opportunities and productivity gains with AI within the scope of client solutions.

🏝️ Benefits

• Health

• Flexible working hours

• Opportunities for professional development