Role Overview
We’re seeking a Senior AI Engineer to lead the design and implementation of advanced AI systems that power intelligent automation and decision-making. In this role, you’ll focus on building production-grade Generative AI and Agentic AI solutions that adapt in real time, solving complex challenges across digital platforms.
Key Responsibilities
- Integrate large language models with external systems, APIs, and databases using secure, efficient orchestration patterns.
- Design and deploy AI-driven workflows that enable autonomous agents to plan, reason, and execute tasks, with support for human-in-the-loop oversight.
- Build and optimize multi-agent architectures using standards like Model Context Protocol (MCP) and modern interoperability frameworks.
- Develop evaluation systems to measure agent performance, autonomy, and safety, ensuring alignment with ethical, security, and moderation policies.
- Apply MLOps and observability practices to monitor AI operations, enabling reliable deployment and continuous improvement.
- Work with data scientists and engineers to select, fine-tune, and validate models tailored to specific agent-based applications.
- Explain AI system behaviors and decisions clearly to both technical and non-technical audiences, fostering trust and transparency.
Required Qualifications
- Proven experience in designing and deploying AI systems, particularly in Generative AI, natural language processing, and LLM integration.
- Strong software engineering background with languages and frameworks such as Python/Django, Java/Spring, or TypeScript/Express.
- Deep understanding of generative model trade-offs and the ability to match models to specific use cases.
- Hands-on experience integrating tools and functions into LLMs using frameworks like MCP.
- Proficiency with data embeddings, vector databases, and chunking strategies to enhance data retrieval and system performance.
- Experience with CI/CD pipelines using tools like GitHub Actions, Jenkins, or Azure Pipelines.
- Familiarity with cloud platforms (AWS, Azure, GCP) and AI services such as AWS Bedrock or Azure AI.
- Experience using evaluation tools like RAGAS, LangSmith, DeepEval, or Braintrust to assess AI performance.
- Knowledge of observability, event tracking, and performance validation in AI systems.
- Strong skills in prompt and context engineering to optimize model behavior across diverse scenarios.
- Ability to communicate complex AI concepts clearly to stakeholders at all levels.
Preferred Qualifications
- Experience with Agentic AI frameworks such as LangGraph, CrewAI, Agent Development Kit (ADK), or OpenAI Agents SDK.
- Background in optimizing machine learning models and integrating AI into large-scale software ecosystems.
- Hands-on experience with containerized deployments using Kubernetes for scalable, reliable AI services.
- Experience designing high-throughput, low-latency data systems with strong security and compliance standards.
Technical Environment
You’ll work with technologies including LLMs, Generative AI, NLP, Model Context Protocol (MCP), Python, Django, Java, Spring, TypeScript, Express, AWS Bedrock, Azure AI Services, cloud platforms (AWS, Azure, GCP), CI/CD tools, vector databases, MLOps, observability platforms, and prompt engineering frameworks.
Work Environment
This role is fully remote for candidates based in Brazil. Those located in São Paulo or Porto Alegre have the option to work from an office on a flexible schedule. We support a globally distributed team with a focus on collaboration, flexibility, and work-life harmony.
Our Culture
We value innovation, engineering excellence, and a people-first mindset. Our teams operate with agility, embrace DevOps principles, and thrive in a growth-oriented environment with international reach. You’ll be part of a diverse, inclusive organization that prioritizes learning, collaboration, and meaningful impact.
Equal Opportunity Employer
We are committed to building a diverse and inclusive workplace. Employment decisions are based on merit, qualifications, and performance, without regard to race, gender, background, or any other characteristic unrelated to professional capability.
