Capco

Security Engineer

• Develop, implement and update the PGR – Risk Management Program, ensuring hazard analysis, risk assessment and definition of control measures.
• Supervise and prepare technical documents such as LTCAT – Technical Report of Working Environmental Conditions.
• Support the preparation and review of other environmental programs and reports.
• Ensure compliance with applicable Regulatory Standards (NRs).
• Monitor legal updates, advise managers and promote corrective and preventive actions.
• Coordinate and provide guidance for trainings required by applicable NRs.
• Plan and conduct internal safety audits.
• Identify non-conformities, opportunities for improvement and critical risks.
• Monitor performance indicators (KPIs) related to health and safety.
• Provide technical analyses for the investigation of accidents and incidents.
• Oversee critical activities, field inspections and work permits.
• Serve as a technical reference for managers and operational teams.
• Participate in the company’s strategic planning process.
• Propose continuous improvement initiatives, investments and safety-related projects.
• Ensure integration of safety management with industry standards and best practices.

Occupational Safety Engineer

Operations

• Support the quality audit process for equipment suppliers;
• Participate in the planning and execution phases of quality audits for equipment suppliers across any equipment category in the Oil & Gas sector;
• Execute scheduled audit planning and programs;
• Monitor and follow up on corrective action plans with suppliers for nonconformities, opportunities for improvement and audit observations;
• Support the process for monitoring quality and manufacturing processes at equipment suppliers;
• Participate in the planning and execution of quality monitoring events at suppliers across any equipment category in the Oil & Gas sector;
• Witness manufacturing inspection events scheduled in the PIT;
• Monitor and follow up on corrective action plans with suppliers for nonconformities identified during monitoring activities;
• Respond to technical queries from suppliers and internal stakeholders;
• Comply with manufacturing inspection schedules and planning;
• Act impartially when evaluating and interacting with equipment suppliers and Inspection Bodies contracted by them;
• Verify suppliers’ and sub-suppliers’ compliance with Petrobras contractual documents;
• Assess manufacturing deviations reported by the Supplier and/or Inspection Body;

Operations Engineer

Backend Engineer

• Evolve and maintain a solution, ensuring quality, performance, security, and scalability.
• Implement and evolve REST APIs using Django REST Framework (versioning, validation, and serialization).
• Develop and maintain scaling features, portfolios and planning history.
• Create and optimize queries and models in PostgreSQL (indexes, transactions, consistent migrations).
• Work with WebSockets (Django Channels) for real-time updates.
• Implement and maintain Excel exports (openpyxl) with complex business rules.
• Integrate and monitor synchronization routines with external systems (e.g., SAP).
• Ensure integrity and security of the permissions and profiles system.
• Contribute to automated tests (pytest / Django unittest) and maintain the agreed minimum coverage.
• Review PRs, propose architectural improvements, and follow internal standards (linting, app structure, internationalization).
• Diagnose and optimize performance bottlenecks (DB, I/O, memory, N+1 queries, WebSockets).
• Gradually evolve the frontend (improve UX, JS modularization, possible future modernization).
• Support the CI/CD pipeline, containerization (Docker / docker-compose), and consistent local execution.
• Document: endpoints, critical flows, technical decisions, and diagrams (C4 / technical READMEs).

Mid-Level Full Stack Developer — Python, Django, Integrations

Engineer

• Database Management: Creation, maintenance, updating and migration of databases used as a knowledge base.
• Field Knowledge Management: Continuous analysis of well intervention data to organize and make information available in a structured way; development of analyses to identify correlations between relevant data for planning and risk assessment; and evaluation of anomalies in interventions to detect trends related to the executed phase, the drilled formation and operational conditions.
• Technical Analysis of Information Entered into the Adopted System(s): Analysis of interventions, communication of discrepancies, assurance of information convergence and requests for implementation of changes in the database.
• Quality Control of Well Intervention Bulletin Databases: Use of Artificial Intelligence and Business Intelligence systems to validate data; recording and maintaining data structuring, taxonomy and ontology; and proposing adjustments to standards and manuals.
• Statistical Database of Operation Times: Creation and maintenance of historical databases for analysis of operation durations, differentiating productive and non-productive times to build probabilistic distributions.
• Support for Intervention Planning: Organization and validation of information for planning future interventions, analysis of inputs, verification of completeness and validation of study start/end dates, simulation of operation durations using specialized software and preparation of reports according to established and validated standards.
• Semiannual and Multiyear Process Control Analysis: Evaluation of the temporal evolution of operations and identification of trends to improve the process.
• Specific Analysis: Detailed study of operation characteristics, durations and anomalies to identify patterns, correlations and trends for a given period, field or basin, which may involve internal or external data.
• Campaign Monitoring: Monitoring campaign progress, updating projections and analyzing deviations from the plan.
• Subsea Operations Performance: Measurement of subsea operation durations segmented according to the established ontology and performance comparisons between service providers, including graphical analyses (boxplots).
• Campaign Planning: Use of the operational knowledge base for duration estimates, planning and technical-economic analysis of campaigns.

Well Engineer

SDET

• As a QA Automation Engineer at Capco, you’ll design, develop, and execute manual and automated test cases for web, mobile and API applications for Wealth & Asset Management platforms.
• You’ll work closely with developers, product and business stakeholders to align testing efforts with project requirements.

QA Automation Engineer

Business Intelligence Analyst

• Prepare and review management dashboards related to indicators and activities of the Supply of Goods and Services process, especially contract management, national and international due diligence, and goods quality management;
• Update dashboards and databases according to the periodicity defined by the client, which may be daily, weekly, biweekly, monthly and/or annually for activities such as purchase order control, claims/requests, amendments, TEP, Ombudsman channels, Supplier Channel and internal tickets and/or internal and external requests;
• Perform critical analysis of the information contained in the dashboards, requiring contact and integration with other areas such as warehouses, contracting, planning, stakeholder/client areas, Finance, Tax, PGEA and other management teams;
• Track, control and monitor tasks derived from action plans resulting from managerial decisions;
• Develop tools for control and traceability of materials, packaging and/or containers, as well as contracts and purchase orders (PCs);
• Develop tools for preparing, reviewing and/or updating information in systems (ServiceNow, SAP HANA, SAP Ariba and purchasing documents such as contracts and/or PCs);
• Other activities necessary to support managerial decision-making related to operational and/or capital goods contracts.

• Implement and optimize LLM agents and AI-driven reasoning flows.
• Develop and maintain backend services that support GenAI applications.
• Create, test, and refine prompts and prompt-engineering strategies for various use cases.
• Integrate grounding logic with graph structures and graph databases.
• Collaborate with graph engineers on modeling, ingesting, and consuming graph data.
• Contribute to the evolution of the GenAI PRT Tool proof of concept (POC), ensuring scalability, performance, and technical quality.
• Participate in architectural and solution-design discussions involving generative AI.

LLM/Backend Developer – Graph Engineer

Full-stack Engineer

• Lead and mentor multidisciplinary engineering teams, fostering a culture of technical excellence, ownership, and continuous improvement.
• Drive the design and implementation of end-to-end solutions using modern architectural patterns, including microservices and cloud-native approaches.
• Serve as a hands-on technical leader, supporting architectural decisions and critical challenges.
• Collaborate with business and product teams to translate requirements into scalable, secure technical solutions.
• Take ownership of technical delivery, ensuring quality, performance, scalability, and reliability in production.
• Define and promote engineering best practices, standards, and guidelines across teams.
• Coordinate development, deployment, and operational activities across multiple teams and systems.
• Support cloud strategy and implementation on platforms such as AWS and Azure.
• Lead technical assessments, proof-of-concepts (PoCs), and adoption of new tools, frameworks, and technologies.
• Ensure alignment with Agile delivery models and actively participate in ceremonies and planning.

Engineering Lead

QA Engineer

• Responsible for defining and leading quality strategies for complex, enterprise-level systems, ensuring high standards of quality, reliability and compliance.
• Lead and mentor QA Engineers, Test Managers and UAT teams, fostering a quality culture and continuous improvement.
• Establish and govern testing practices covering unit, integration, system, UAT, performance and non-functional testing.
• Design and drive execution of automated and manual testing strategies for web, mobile, microservices and desktop applications.
• Define and implement frameworks for test data management, test environments and QA governance.
• Partner with engineering, architecture and product teams to embed quality throughout the software development lifecycle.
• Manage defect processes, metrics, reporting and executive communication on quality status.
• Lead planning, execution and reporting of UAT in collaboration with technical and business stakeholders.
• Identify process inefficiencies and lead QA transformation initiatives using data, metrics and continuous feedback.
• Support compliance and quality requirements in regulated environments such as banking and financial services.

QA Lead

Manager

• Own end-to-end delivery of technology and digital transformation initiatives, ensuring scope, schedule, budget and quality.
• Lead and coordinate cross-functional teams, including architects, engineers and Agile roles, fostering a high-performance culture.
• Implement and evolve Agile and hybrid delivery models aligned with organizational maturity and business objectives.
• Act as the primary point of contact for senior stakeholders, ensuring transparency, alignment and effective communication.
• Manage delivery risks, dependencies and impediments, driving resolution and escalation as needed.
• Ensure operational efficiency and continuous improvement in delivery processes.
• Support financial management of deliveries, including forecasting, budget monitoring and resource allocation.
• Drive innovation and technological evolution in partnership with architecture and engineering leaders.
• Facilitate governance forums, delivery reviews and executive reporting.
• Coach teams and leaders on Agile practices and delivery best practices.

Delivery Manager

• Lead the design, implementation, and maintenance of advanced test automation frameworks for microservices.
• Execute stress, load, regression, and integration tests to ensure performance and reliability.
• Develop and execute comprehensive test plans and test cases for microservices architectures.
• Use tools such as JFrog for artifact management and deployment validation.
• Use JMeter to simulate complex performance and load scenarios.
• Collaborate with backend developers and DevOps engineers to integrate tests into CI/CD pipelines.
• Analyze and report test results, identifying bottlenecks and areas for improvement.
• Drive continuous improvement initiatives for QA processes and tools.

Senior QA Engineer, Automation

Data Scientist

• Define and lead data architecture and strategy across analytical, operational, and integration platforms.
• Lead and mentor data engineers, architects, and analytics teams, promoting technical excellence and best practices.
• Design and oversee end-to-end data solutions: ingestion, processing, modeling, and consumption layers.
• Drive data integration initiatives between heterogeneous systems, cloud platforms, and third-party solutions.
• Ensure data governance, data quality, metadata management, and lifecycle practices.
• Act as a technical advisor to stakeholders, translating business requirements into scalable and secure solutions.
• Oversee the design and implementation of BI, analytics, and reporting solutions to support strategic decision-making.
• Manage dependencies, risks, and technical decisions in complex, data-intensive projects.
• Collaborate with architecture, engineering, security, and business teams to ensure alignment and delivery.
• Actively participate in Agile ceremonies and contribute to continuous improvement initiatives.

Data Lead

• Design, develop, and maintain robust, scalable web applications across frontend and backend layers.
• Contribute to the modernization of legacy systems, enabling integration with modern platforms, APIs, and services.
• Integrate APIs, machine learning models, and AI services into applications to extend functionality and automation.
• Collaborate with data scientists, machine learning engineers, and platform teams to deliver AI-driven solutions.
• Participate in the design and architecture of modernization and AI-based solutions, ensuring scalability, security, and maintainability.
• Apply best practices for clean code, version control, automated testing, documentation, and CI/CD.
• Explore, prototype, and apply solutions using Generative AI, NLP, computer vision, and intelligent automation according to project needs.
• Support gradual migration and coexistence of legacy and modern technologies, ensuring stability and business continuity.
• Actively participate in Agile ceremonies and contribute to continuous improvement initiatives.

Senior Fullstack Developer, AI

DevOps Engineer

• Design, implement, and continuously improve CI/CD pipelines to support frequent, reliable deliveries.
• Enable development teams with self-service tools and automation to reduce manual operations.
• Collaborate with developers, QA, and architects to improve delivery speed and system reliability.
• Support the design and operation of cloud, on-premises, or hybrid environments.
• Apply Infrastructure as Code (IaC) principles to provision and manage environments consistently.
• Ensure environments are reproducible, scalable, and aligned with security and compliance requirements.
• Improve system reliability, availability, and performance.
• Implement and evolve monitoring, logging, alerting, and tracing strategies.
• Participate in incident response, post-incident analysis, and root-cause investigations.
• Define SLOs, SLIs, and operational best practices.
• Embed security by design into pipelines and infrastructure (DevSecOps).
• Support access control practices, secrets management, and secure configuration.
• Collaborate with security teams to meet organizational and regulatory requirements.
• Promote a DevOps culture: automation, ownership, collaboration, and continuous improvement.
• Identify bottlenecks in development and delivery processes and propose pragmatic solutions.
• Document processes, standards, and architectural decisions.
• Mentor and support teams in adopting DevOps best practices.

DevOps SME

• Consultant/developer mindset, able to balance deep technical expertise with clear client communication
• Strong learning agility, demonstrated by past experience and a continued willingness to grow in this area
• Willingness to learn and work with new programming languages, particularly legacy languages (COBOL, Natural Adabas, PL/I and many others)
• Ability to analyze transformation and code-generation pipelines (ASTs, IRs, parsers, transpilers), or strong potential to specialize in this area
• Knowledge of design patterns and design systems to support efficient evolution, analysis, assessment, and reuse of workflows as well as both client and target code
• Understanding of code modernization and refactoring strategies (re-hosting, re-platforming, re-architecting)
• Strong problem decomposition and abstraction skills in heterogeneous systems
• Excellent communication skills and autonomy to lead client presentations, gather feedback, and manage expectations.