AI Solutions Architect - Platform Enablement Specialist

New

BrazilFull-TimeSenior

Salary not disclosed

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Job Details

Proven experience working with enterprise-scale AI/ML platforms in production environments.
Deep understanding of AI agents, large language models (LLMs), and workflow orchestration patterns.
Strong background in technical enablement, developer advocacy, solution architecture, or AI platform adoption initiatives.
Ability to create comprehensive technical documentation and conduct effective knowledge-sharing sessions with engineering teams.
Strong autonomy and problem-solving capabilities, with the ability to independently identify challenges and execute solutions.
Hands-on experience with cloud platforms such as AWS, Azure, or GCP in AI/ML contexts.
Practical experience with AI agent frameworks such as LangChain, LangGraph, CrewAI, AutoGen, or similar technologies.
Familiarity with MLOps platforms and tools including MLflow, Vertex AI, SageMaker, or Kubeflow.
Experience working within agile product teams and fast delivery cycles.
Excellent communication and collaboration skills.

Lead technical enablement initiatives for engineering and product teams adopting AI platforms and agent-based architectures.
Drive the adoption and scalability of AI development components, workflows, and deployment standards across multiple teams and projects.
Coordinate and execute migrations of legacy AI solutions into modern enterprise AI platforms and ecosystems.
Identify technical gaps, bugs, documentation issues, and adoption barriers, proactively proposing and implementing improvements.
Create high-quality technical documentation, including reference architectures, implementation guides, runbooks, and code examples.
Translate feedback from internal communities and platform users into actionable insights for product and engineering teams.
Serve as the primary technical liaison between platform teams and engineering stakeholders, ensuring alignment and platform evolution.
Support the establishment of best practices for AI governance, orchestration, scalability, and operational excellence.

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