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I

AI Engineering Specialist

Internas

AI Engineering Specialist leading development of high-impact AI solutions. Collaborating cross-teams to ensure economic and technical governance of AI models.

Posted 7/3/2026full-timeRemote • 🇧🇷 BrazilMid-LevelSeniorWebsite

Core Competencies

Role fit
Core Competencies

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Demonstrates expertise in generative AI, LLMs, and natural language processing, with a strong focus on designing scalable AI engineering frameworks and ensuring technical governance. Proficient in backend development and orchestrating complex workflows using code-first frameworks.

Highest-signal resume keywords
Generative AI ExperienceNatural Language Processing (NLP)Backend Development (Python)Vector Databases and EmbeddingsAI Engineering Framework Design

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills
Generative AILLMsNatural Language Processing (NLP)Backend DevelopmentMicroservicesEvent-Driven ArchitecturesPrompt EngineeringContext EngineeringCode-First FrameworksCI/CD Pipelines
Tools & Technologies
AWS Cloud GovernanceLangGraphLangChainSemantic KernelGraphRAGCrewAIAutogen
Industry Keywords
AI Engineering StandardsSpec-Driven Development (SDD)Intent DevelopmentHarness EngineeringTechnical Governance

Tech Stack

Tools & technologies
AWSCloudPython

About the role

Key responsibilities & impact
  • Define the long-term architectural vision and AI engineering standards for high-criticality systemic products.
  • Lead the evangelization, design, and structuring of a cross-team ecosystem for native AI development, including scalable practices for SDD (Spec-Driven Development), Intent Development, and Harness Engineering.
  • Ensure technical and economic governance of AI models, balancing token costs, latency, security (corporate guardrails), and data privacy.

Requirements

What you’ll need
  • Proven experience in generative AI, LLMs (Claude, GPT, Gemini, etc.), virtual assistant development, and natural language processing (NLP).
  • Hands-on experience with vector databases, embeddings, RAG (including GraphRAG), prompt engineering, and context engineering.
  • Experience orchestrating agents using code-first frameworks (LangGraph, LangChain, Semantic Kernel, Strands, CrewAI, Autogen, or similar), building multi-step/multi-agent workflows with function calling and structured outputs.
  • Strong backend development experience (Python or similar), microservices, event-driven architectures, AWS cloud governance (ECS, security, observability), and advanced model benchmarking/monitoring.
  • Experience designing and developing internal AI engineering frameworks, libraries, or platforms for use by other teams.
  • Mastery of code-agent-assisted workflows, standardization of Agent Skills, SDD (Spec-Driven Development), and Intent Development as robust architectural contracts interpretable by autonomous agents.
  • Ability to design platform-level Harness Engineering infrastructures, including CI/CD pipelines for continuous semantic validation of coding agents.

Benefits

Comp & perks
  • We value the continuous growth of zuppers, encouraging each person to pursue paths that drive their professional development.