Brazil
Jitterbit
Keyrus Brazil
Forward Deployed Engineer – Architect of Intelligence
Brazil
São Paulo, São Paulo, Brazil
Automatic translation. Check the original.
About the opportunity
Why Keyrus, Why Now!
Keyrus is an international group with 2,800 consultants and specialists in 28 countries, built on a conviction: AI does not transform companies. Architected intelligence transforms.
For over 30 years, we have been building the data foundations that make intelligent systems possible, designing the Intelligent Enterprise Operating System, where intelligence is embedded into the core of business processes to create sustainable value: we operationalize intelligence.
AI does not replace humans. It repositions us in a place no system can reach: to understand, decide, create, and innovate.
At Keyrus, you will not just develop skills; you will develop discernment. Your expertise strengthens with every system you design, every business challenge you help solve, and every implementation that evolves from prior learnings.
Over time, you will become one of the rarest professionals of the intelligence era: someone capable of connecting data, AI, and human decision-making at scale, across different sectors, markets, and geographies.
This is not just a position. It is a discipline you master and a story you help write to become a Keyrus Architect of Intelligence.
Technology amplifies capabilities. Keyrus culture differentiates. Excellence in execution connects both.
WHAT YOU WILL ARCHITECT
As a Forward Deployed Engineer, you will work closely with the client's technical and business teams to take an agreed AI opportunity from technical discovery through to deployment and operationalization for users.
You will translate business requirements and approved architecture into a practical technical delivery plan, coordinate necessary engineering competencies, contribute directly to implementation, and integrate the solution into the client's real environment.
Within agreed business outcomes and target architecture, you will make day-to-day decisions about technical scope, implementation sequence, integration, and deployment.
You will engage with AI Engineers, Software Engineers, Data Engineers, AI Platform Architects, Governance specialists, and Service Delivery teams, without replacing their specialized responsibilities.
This is a hands-on engineering role. It is not a pure coordination position.
Your responsibilities
- Lead technical discovery for selected use cases — working with client teams to understand systems, data, security, identity, workflows, dependencies, technical constraints, and production requirements.
- Translate the agreed use case and target architecture into technical scope and practical delivery sequence — defining what needs to be built, integrated, validated, and deployed, and in what order.
- Build and adapt production solution components as needed — applying hands-on engineering to connect APIs, applications, AI services, data sources, enterprise systems, workflows, identity, and other client environment dependencies.
- Coordinate engineering specialist contributions across the solution — working with AI, Software, Data, Platform, Security, and Governance specialists, preserving their technical responsibilities and resolving inter-area blockers.
- Own the technical deployment and operationalization of the solution within agreed scope — bringing it to the client environment, coordinating environments and dependencies, validating production readiness, and adapting the implementation based on real constraints.
- Work directly with client users and technical teams during deployment — validating solution operation in real workflows, resolving technical barriers to adoption, and enabling client teams to use and sustain what has been deployed.
- Transparently manage technical delivery decisions and risks — maintaining clarity on scope, sequence, dependencies, architectural exceptions, production issues, and decisions requiring escalation to the relevant specialist or business owner.
- Ensure sustainable transition and reuse what works — documenting the deployed solution, operational dependencies, technical decisions, operational requirements, and reusable patterns that strengthen future Keyrus projects.
- Value and ROI measurement — conceived and tracked in production, including inference costs.
- First measurable outcome in weeks — maximum autonomy from day one at the client.
WHO YOU ARE
You are a hands-on engineering individual, comfortable with both client proximity and technology.
You thrive in environments where the problem is not yet fully defined, documentation may be incomplete, systems do not connect easily, and the path to production needs to be discovered during delivery.
You know how to write and debug production code, but your value extends beyond programming. You understand how applications, AI capabilities, data, APIs, cloud environments, identity, security, governance, and business processes connect.
You know when to solve something directly and when to involve a subject matter expert.
You are confident making implementation decisions within your autonomy and escalating architectural, business, governance, or domain decisions to the appropriate owners.
You build trust through technical credibility, agility, transparency, and the ability to make complex systems work in real-world environments.
WHAT YOU BRING
Experience and Qualifications
- Solid hands-on experience building, integrating, and deploying software, AI, data, or cloud solutions into production, in complex environments.
- Strong engineering capability in at least one relevant programming ecosystem, with the ability to write, review, debug, and adapt production-quality code.
- Proven experience working directly with clients, users, or complex stakeholder environments, maintaining technical ownership.
- Solid experience in system integration via APIs, services, data interfaces, authentication/identity, cloud services, or equivalent enterprise integration patterns.
- Ability to translate ambiguous requirements into clear technical scope, implementation sequence, and production deployment plan.
- Hands-on experience deploying into real production environments, diagnosing blockers, managing technical dependencies, and adapting delivery based on field observations.
- Exposure to client decision-makers — acting as a trusted advisor to executives, as well as users and IT teams.
Preferred Requirements
- Hands-on knowledge of generative AI, RAG, agents, model APIs, and AI-enabled workflows, sufficient to integrate AI capabilities and collaborate effectively with AI Engineers.
- Experience in at least one major cloud or enterprise technology ecosystem, with the ability to operate in comparable environments.
- Familiarity with software engineering practices, including testing, Git, CI/CD, containers, observability, security, and production operations.
- Experience coordinating multi-disciplinary technical work involving AI, Software, Data, Platform, Security, Architecture, or Governance.
- Experience supporting technical adoption through pair work, enablement, documentation, training, or close collaboration with client engineering and operations teams.
- Strong ability to communicate technical trade-offs, dependencies, risks, and decisions to non-specialist engineers and stakeholders.
Differentiators
- Deep experience in AI Engineering, including RAG, agents, evaluations, model integration, or agentic workflows.
- Experience in full-stack or backend application engineering.
- Experience in Data Engineering or Cloud/Platform Engineering.
- Experience in regulated, security-sensitive, or highly complex enterprise environments.
- Experience with solution architecture or technical design responsibilities.
- Experience in consulting or professional services for multiple clients.
- Experience creating reusable technical accelerators, reference implementations, deployment patterns, or field engineering guides.
- Experience in formal Forward Deployed, Customer Engineering, Deployment Engineering, or similar client-integrated engineering models.
WHAT WILL MAKE YOU SUCCEED
- You easily translate ambiguous situations into a concrete technical plan.
- You maintain hands-on engagement without losing sight of the full deployment.
- You make technical scope, sequence, dependencies, and responsibilities explicit.
- You know when to make a decision and when to involve the right specialist.
- You pragmatically resolve integration and production blockers.
- You stay close to real users and client technical teams during deployment.
- You measure success by an operational solution that can be adopted and sustained, not just by project tasks completed.
- You transform field experience into reusable knowledge for future deliveries.
OUR VALUES
Collective Intelligence
Collaboration across different specialties, roles, and geographies allows us to combine knowledge and deliver more complete answers to our clients' challenges.
Reliability
The ability to deliver complex projects with rigor, quality, and consistency is a cornerstone of our relationship with clients and partners.
Pragmatism
We prioritize concrete impact and measurable value over abstract technological discourse.
Entrepreneurial Spirit
Curiosity, energy, autonomy, and initiative are the foundation of our culture and drive continuous innovation.
Come join the Keyrus Team!
For more information: keyrus.com.br
We wish you good luck! 😊🚀
ABOUT KEYRUS
At Keyrus, we help organizations evolve from experimental AI to industrialized AI, from isolated agents to orchestrated systems, and from insights to execution.
This is the discipline we call Architect of Intelligence: designing the intelligent enterprise operating system, where intelligence is embedded into business processes to create sustainable value.
Driven by our proprietary Human Orchestrated Model™ (HOM), we structure intelligence foundations, human-centric governance, and performance steering to create intelligent environments where technology amplifies human capabilities.
With over 30 years of experience and 2,800 employees across 28 countries, we help organizations go beyond transformation, building adaptable, resilient, and continuously evolving companies.
AI does not transform businesses. Architected intelligence transforms.
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