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CI&T

Senior AI Engineer

CI&T

. Architect and build client software solutions from architecture through tested code .

Posted 11/9/2026full-timeRemote • Brazil, ColombiaSeniorWebsite

Core Competencies

Role fit
Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in architecting and building scalable software solutions using modern software architecture principles, while ensuring compliance with ethics, privacy, and data security standards. Proficient in managing context data pipelines and implementing observability instrumentation to enhance system performance.

Highest-signal resume keywords
Software ArchitectureAgentic SDLCMicroservicesFoundation Model APIsObservability Instrumentation

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills
Software DevelopmentToken Economy DecisionsTestingRed TeamingAutomationCI/CDTDDData SecurityModel Fine-TuningEvent-Driven Systems
Soft Skills
MentoringCollaborationCritical Review
Tools & Technologies
Runtime FrameworksTool OrchestrationVector DatabasesInternal Data SourcesSystem Prompts
Industry Keywords
EthicsPrivacyComplianceAI-Assisted DevelopmentContext Data Pipelines

Tech Stack

Tools & technologies
MicroservicesSDLC

About the role

Key responsibilities & impact
  • Architect and build client software solutions from architecture through tested code
  • Build, customize, and orchestrate agents, skills, subagents, commands, and harnesses
  • Reuse development agents and harnesses across the team to modernize software development and reduce lead time
  • Apply modern software architecture and engineering fundamentals to build, assess, and critique code and solutions
  • Translate functional requirements into viable, simple, and scalable technical solutions
  • Design and assess solutions, agents, and skills using evals, tests, and red teaming
  • Make token economy decisions to balance solution quality and inference cost
  • Architect and build agentic solutions using foundation-model APIs, RAG, tool orchestration, runtime frameworks, prompts, and guardrails
  • Manage engineering and context data pipelines integrating internal sources and vector databases
  • Implement application and agent observability instrumentation and monitor system behavior
  • Review and critique AI-generated outputs against technical, quality, and business requirements
  • Delegate specialized tasks to agents while maintaining technical depth in the specialty stack
  • Deliver production-ready solutions aligned with deployment and operation requirements
  • Apply ethics, privacy, data security, and compliance practices
  • Lead solution design for complex problems and own solutions end to end
  • Establish reusable agents, skills, and harnesses across the team
  • Guide prompt engineering, evals, and red teaming decisions
  • Mentor peers, review code and standards, and collaborate with AI Deployment Engineers and AI Orchestrators

Requirements

What you’ll need
  • Experience architecting and building software solutions from architecture through tested code
  • Ability to work in any technology stack
  • Experience using agentic SDLC and AI-assisted software development
  • Knowledge of modern software architecture and engineering fundamentals
  • Experience with microservices, event-driven systems, queues, CI/CD, TDD, and automation
  • Ability to translate functional requirements into simple, scalable technical solutions
  • Experience designing and assessing solutions and agents with evals, testing, and red teaming
  • Knowledge of hallucinations, prompt injections, and data leaks
  • Ability to make token economy decisions involving context size, RAG strategy, and agent calls
  • Experience with foundation model APIs, RAG, tool orchestration, orchestration and runtime frameworks, system prompts, and guardrails
  • Experience managing context data pipelines, internal data sources, and vector databases
  • Experience implementing observability instrumentation in applications and agent code
  • Ability to critically review AI-generated outputs
  • Knowledge of ethics, privacy, data security, and compliance practices
  • Ability to fine-tune models rather than train them from scratch

Benefits

Comp & perks
  • Health and dental insurance
  • Meal and food allowance
  • Childcare assistance
  • Extended paternity leave
  • Partnership with gyms and health and wellness professionals via Wellhub (Gympass) TotalPass
  • Profit Sharing and Results Participation (PLR)
  • Life insurance
  • Continuous learning platform (CI&T University)
  • Discount club
  • Free online platform dedicated to physical, mental, and overall well-being
  • Pregnancy and responsible parenting course
  • Partnerships with online learning platforms
  • Language learning platform
  • Inclusion support and accommodations during the selection process
  • Dedicated Health and Well-being team, inclusion specialists, and affinity groups