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Senior MLOps / LLM Engineer

Senior MLOps / LLM Engineer

Acendeosuzano, estado de são paulo, br
Há 16 dias
Descrição da vaga

Description

We’re seeking an experienced DevOps / LLMOps or MLOps / LLMOps Engineer to design, deploy, and maintain the infrastructure supporting Large Language Model (LLM) platforms. This role blends DevOps best practices with AI / ML expertise, with a focus on building and scaling agentic AI systems that integrate directly with LLMs. You’ll drive development of intelligent, autonomous agents while ensuring reliability, scalability, and performance across training, fine-tuning, and deployment pipelines.

English fluency is a MUST for this role! Only candidates with level C1 or C2 will be considered :

  • A1 Beginner
  • A2 Elementary
  • B1 Intermediate
  • B2 Upper-Intermediate
  • C1 Advanced
  • C2 Proficient

Responsibilities

  • Own strategy and execution of agentic AI systems using LLMs and autonomous decision-making components
  • Build prototypes and scale them into MVPs demonstrating real-world AI viability
  • Collaborate with engineering and product teams to embed LLM agents into user-facing features
  • Design and manage CI / CD pipelines for LLM training and deployment workflows
  • Provide technical leadership on DevOps, security, and deployment strategies for AI / ML models
  • Requirements

  • 5+ years building and deploying ML or GenAI systems in production, with strong architectural and systems-level ownership
  • 2+ years of proven experience with LLM integration, LLM-based agents, or autonomous reasoning systems
  • End-to-end AI / ML delivery : data prep, training, evaluation, deployment, monitoring
  • Cloud expertise (AWS, GCP, or Azure) with CI / CD pipelines, multi-tenant deployments, and infrastructure automation
  • Experience with Databricks and familiarity with Langchain / GenAI toolkits
  • Strong agility and ability to deliver in fast-moving product environments
  • Nice To Have

  • Advanced degree (MS / Ph.D.) in ML, Computer Science, or related field
  • Deep expertise in DevOps / MLOps practices and scaling secure, enterprise-grade AI workflows
  • Broader data engineering knowledge, especially in Databricks
  • Background in aviation industry
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