Artificial Intelligence

• Configure and customize agentic tools — including GitHub Copilot (agent and plan modes) — to fit the squad's specific context, codebase, and delivery standards.
• Design and maintain integration roadmaps that define how AI capabilities plug into each stage of the SDLC, from requirements and technical solution through development, testing, code review, and deployment — without disrupting the client's existing, mature DevOps pipeline.
• Ensure output quality upstream and downstream: review, validate, and refine what AI agents produce at each stage, identifying deviations early and adjusting configurations, prompts, and guardrails to keep quality consistent and trustworthy.
• Build and refine prompt engineering assets — including specification prompts, code generation instructions, test generation templates, and documentation workflows — tailored to the squad's architecture and ways of working.
• Conduct tooling audits and support value stream mapping sessions, identifying bottlenecks in the SDLC where the right agentic capability can eliminate waiting time and reduce lead time.
• Define and implement guardrails and ethics and compliance standards for AI usage within the development workflow, ensuring responsible and governed adoption aligned with the client's policies.
• Pair daily with developers, QAs, and BAs to embed agentic practices into real work items, coaching team members on effective agent use and gradually transferring ownership as the squad gains autonomy.
• Develop and maintain technical documentation that captures agent configurations, integration patterns, and best practices, feeding both the squad's day-to-day operations and the final Agentic SDLC Playbook.
• Continuously monitor AI system performance — adoption rates, output quality, cycle time impact — and iterate on configurations to drive measurable improvements every two-week cycle.
• Support problem-solving at the intersection of AI tooling and software delivery, acting as the technical reference when agents produce unexpected results or when new SDLC stages need to be instrumented.

AI Orchestrator, Squad Leader

• Manage the members of the software development team with the goal of coaching and developing our employees (individual development plans), conducting one-on-one (1:1) sessions, establishing action plans, and giving frequent feedback.
• Guide your team members in adopting agile practices, facilitating ceremonies that are part of the squad’s methodology, such as plannings, refinements, retrospectives, etc.
• Remove impediments for the team.
• Foster an environment of respect and trust together with team members, adapting your leadership style to different situations.
• Navigate the company to identify opportunities and key roles for the team’s success.
• Coordinate initiatives that require one or more teams for the product’s success.
• Hold sessions with all types of stakeholders to present recent results, gather feedback/insights, and align on the product roadmap.
• Ability to present complex technical information clearly and concisely to all types of stakeholders.
• Build the squad’s vision and mission together with team members.
• Regularly monitor product metrics, business metrics, and technical indicators—questioning, improving, and providing visibility into the team’s objectives and initiative statuses.
• Participate in product discovery processes, problem mapping, and incident resolution.
• Contribute to defining the product/squad objectives and key metrics, frequently communicating these results to stakeholders (OKRs).
• Establish a software development process and maintain a steady and healthy pace.
• Handle competing needs/priorities, taking on responsibilities and risks in a fast-paced, constantly changing environment.

Tech Manager I – Gen AI, Relationship RE, Direct Sales

• Review AI-generated responses for clarity, accuracy, correctness, relevance, and overall quality.
• Annotate and label language content according to detailed project guidelines.
• Generate or evaluate prompts based on assignment requirements.
• Identify linguistic errors, dataset concerns, and structural inconsistencies.
• Provide clear, structured feedback to support improvements in AI performance.
• Communicate complex language requirements clearly to both linguistic and non-linguistic stakeholders.
• Collaborate with QA Leads and clients to apply feedback and maintain quality standards.
• Participate in required client-facing meetings with your camera on.
• Submit daily work reports and consistently meet productivity and quality expectations.

AI Evaluation & Annotation Reviewer, L3 – Advanced Level – Portuguese

• Evaluate AI-generated responses using professional email history and account activity.
• Assess outputs for **accuracy, relevance, helpfulness, and personalization quality**.
• Identify unsupported assumptions, incorrect personalization, and irrelevant recommendations.
• Compare multiple responses and select the stronger overall result.
• Provide clear and structured evaluation feedback.
• Follow detailed project guidelines and quality standards.
• Maintain confidentiality and follow all data privacy requirements.
• Complete assigned evaluations accurately and within project timelines.

German Business Account Evaluator – AI Personalization

• Support the AI Committee in defining Toledo's initial AI roadmap.
• Contribute to the AI policy that is currently under review.
• Support the form and process by which business areas will request AI solutions.
• Help assess whether requests make sense from a business perspective.
• Help verify whether initiatives generate productivity, operational efficiency, or real value.
• Support best practices, governance, and security to prevent undue exposure.
• Support defining the conditions for the use and potential publication of agents in Copilot Studio.

Artificial Intelligence Specialist – Business Insight

Japanese Business Account Evaluator – AI Personalization

• Structure and manage the commercial pipeline for SAP BTP/BTM + AI, ensuring predictability and accuracy in sales forecasting
• Work across the full consultative sales cycle, from prospecting and qualification to proposal presentation and closing
• Maintain close relationships with strategic customers and partners within the SAP ecosystem
• Collaborate with pre-sales, marketing and delivery teams to ensure differentiated, high-value proposals
• Define sales metrics, reports and KPIs, presenting results to leadership
• Represent Seidor at events, forums and initiatives in the SAP ecosystem

Sales Executive, SAP BTP/BTM, AI

• Review biochemical datasets, protocols, and research findings.
• Evaluate AI-generated content for scientific accuracy and clarity.
• Develop realistic use cases, scenarios, and training materials.
• Identify factual errors, ambiguities, and missing scientific context.
• Provide structured feedback to improve AI response quality.
• Explain complex biochemical concepts in clear, accessible language.
• Apply current biochemistry methods and research standards.
• Participate in iterative content review and validation.

Biochemistry Specialist – AI Training Project

• Review neuroscience data, research, and case studies for accuracy and relevance.
• Evaluate AI-generated content related to neuroscience.
• Create clear explanations, annotations, and scientific commentary.
• Develop or assess scenario-based questions and exercises.
• Identify factual errors, inconsistencies, and unsupported conclusions.
• Apply current neuroscience theories, methods, and research standards.
• Provide structured feedback to improve content quality.
• Contribute practical examples of neuroscience applications in real-world settings.

Neuroscience Specialist – AI Training Project

• Review molecular biology data, protocols, and scientific literature.
• Evaluate AI-generated content for scientific accuracy and clarity.
• Create explanations, annotations, and reference materials.
• Develop realistic questions, scenarios, and datasets.
• Identify factual errors, inconsistencies, and unsupported conclusions.
• Provide structured feedback to improve AI response quality.
• Apply current molecular biology methods and research standards.
• Contribute insights on emerging techniques and applications.

Molecular Biology Specialist – AI Training Project

• Review pharmacology content for scientific accuracy, clarity, and practical relevance.
• Evaluate AI-generated responses to pharmacology and drug-therapy questions.
• Develop realistic cases involving pharmacokinetics, pharmacodynamics, and therapeutic use.
• Create and curate structured pharmacology datasets and reference materials.
• Identify factual errors, unsupported conclusions, and missing clinical context.
• Provide detailed feedback to improve AI reasoning and answer quality.
• Explain complex pharmacological concepts in clear and accessible language.
• Apply current drug-safety principles, regulatory guidance, and clinical standards.
• Document the methodology and rationale behind evaluations and recommendations.
• Collaborate with multidisciplinary teams to improve project guidelines and content quality.

Pharmacology Specialist – AI Training Project

• Responsible for mapping processes across all company areas, identifying bottlenecks, rework, and repetitive activities.
• Evaluate processes eligible for AI automation, produce functional documentation and BPMN flows, and define functional requirements for agent development.
• Prioritize the AI initiatives backlog.
• Measure gains achieved (time, cost, quality, and productivity).
• Collaborate with business and IT departments.
• Support change management and adoption of the agents.

AI Process Analyst – AI Process Analyst

• Administer the company's enterprise AI platforms - Claude Enterprise, ChatGPT Enterprise, Gemini, and new tools as we adopt them - covering provisioning, access, RBAC, usage governance, and billing, and automate that administration down over time.
• Keep the SVP of Innovation organized and ahead of schedule through prioritization, prep, and follow-through - you catch what would otherwise slip before it does.
• Run the Innovation team's weekly operating rhythm and keep the roadmap current and trusted at all times.
• Produce a weekly AI intelligence brief on what is shipping at the frontier and what the team should test.
• Bring a point of view into strategy conversations and grow into a genuine strategic voice for the team.
• Utilize and leverage Power Digital's Nova ecosystem as it relates to your department.
• Other applicable or related duties as assigned.

AI Operations Manager

• Draft practical templates and examples of commercial agreements.
• Create and review Master Services Agreements and related service contracts.
• Prepare lease, IP licensing, marketing, and general licensing agreements.
• Adapt legal documents to realistic business scenarios and transaction structures.
• Annotate agreements where required to explain clauses, risks, or drafting choices.
• Ensure submissions reflect current legal standards and accepted commercial practice.
• Review documents for consistency, clarity, structure, and legal accuracy.
• Deliver well-organized materials suitable for use in an AI training dataset.
• Clarify project requirements and respond to feedback on submitted documents.
• Ensure all materials are free from confidential or restricted information.

Commercial Contract Specialist – AI Training Project

• Gather requirements from business areas and translate them into AI-based technological solutions.
• Assist users with prompt construction, use of Copilot Studio, and address questions about implemented solutions.
• Develop and support the integration of AI solutions with existing platforms (Microsoft 365, Power Platform, Azure, and corporate systems).
• Contribute to process automation using AI technologies, aiming to optimize and improve the efficiency of internal processes.
• Conduct training sessions, workshops, and knowledge-sharing activities on Artificial Intelligence to promote internal upskilling.
• Actively participate in identifying business opportunities, proposing improvements and innovations that add value to the organization.
• Collaborate on fine-tuning and consuming ready-made LLMs via API, combining the use of pre-trained models and adjustments when necessary.

Senior Artificial Intelligence Analyst

• Design and evolve Artificial Intelligence governance models for organizations across different industries
• Define and implement processes, policies, frameworks, and standards for the development and operation of AI solutions
• Support management of the AI initiative portfolio, prioritizing use cases based on business value, complexity, and risk
• Develop and monitor adoption, usage, efficiency, ROI, and value-generation metrics for AI initiatives
• Support defining governance models for AI agents, copilots, virtual assistants, and generative AI solutions
• Conduct risk assessments related to ethics, privacy, security, compliance, and responsible AI use
• Define approval, validation, and monitoring workflows for AI models and agents
• Facilitate executive forums, committees, and governance ceremonies involving business, technology, and leadership stakeholders
• Produce executive materials, presentations, dashboards, and reports to track initiatives
• Support defining adoption, communication, and change management strategies related to AI
• Work closely with Data, Engineering, Architecture, Security, Legal, and Business teams to ensure integrated governance
• Identify opportunities for continuous improvement and maturation of AI capabilities

AI Governance Analyst

• Software Delivery Management: Plan and monitor software deliveries, ensuring deadlines and quality standards are met.
• Agile Methodology: Facilitate the adoption of agile processes within the team, promoting continuous improvement and efficient sprint execution.
• Roadmap Development: Collaborate with stakeholders to define and prioritize the product roadmap, aligning features with user and market needs.
• MVP: Apply Minimum Viable Product (MVP) principles to quickly validate ideas and iterate based on user feedback.
• Team Leadership: Motivate, coach and develop the team, fostering a collaborative, high-performance environment.
• Scrum Ceremonies: Facilitate ceremonies such as planning, reviews, retrospectives and daily stand-ups to ensure team transparency and progress.

AI Orchestrator

• Lead the definition and evolution of software architecture for Artificial Intelligence-based solutions, including projects involving LLMs
• Design scalable, resilient, and secure architectures, ensuring high performance and availability of applications
• Define standards, best practices, and technical guidelines for developing AI solutions
• Serve as a technical reference for multidisciplinary teams (engineering, data, AI, and product)
• Support the design of end-to-end solutions, from data ingestion to the delivery of intelligent applications in production
• Ensure architecture governance, promoting consistency, quality, and adherence to defined guidelines
• Evaluate and select technologies, frameworks, and architectures suitable for the AI and LLMs ecosystem
• Guide the design of integrations with AI models (APIs, pipelines, and services)
• Define strategies for scalability, cost, and performance for AI-based solutions
• Promote best practices for security, privacy, and responsible use of AI
• Support and mentor developers and technical teams, raising the team’s technical maturity

Software Architect, Artificial Intelligence

• Write and edit core communication materials in various formats
• Contribute to the development of visual and video content
• Support the creation of customer success stories and case studies
• Keep abreast of developments in AI and related technologies
• Coordinate with marketing teams to align messaging across channels

Manager, AI and Innovation Communications

• Build AI-native software
• Drive agents and LLMs based on specifications
• Lead the Spec-Driven Development cycle
• Calibrate AI progressive autonomy
• Participate in the Augmented Pull Request process
• Contribute to the knowledge layer and reusable contexts
• Apply architecture and engineering best practices
• Ensure quality and efficiency
• Work in collaborative, value-driven teams

Artificial Intelligence jobs in Brazil

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