Senior AI Engineer (LLMs & Agentic AI)

Accountabilities: • Build, maintain, and enhance Model Context Protocol (MCP) servers, tool definitions, and context management capabilities, including personally developing MCP servers from the ground up.

• Design and implement intent classification, evaluation, and routing workflows for natural language applications, ensuring requests are directed to the appropriate APIs and data sources.

• Develop multi-step orchestration workflows that coordinate multiple tools, APIs, and data sources, aggregating results into reliable responses.

• Integrate hosted large language models from providers such as Anthropic and OpenAI into production environments.

• Design and manage prompt engineering practices, prompt versioning, fallback strategies, and optimization initiatives to improve performance, latency, and cost efficiency.

• Develop and maintain LLM evaluation frameworks to measure model quality, validate behavior, and monitor production performance.

• Write and optimize SQL queries against cloud data warehouses to analyze model inputs and outputs and support evaluation and monitoring.

• Support backend functionality for conversational interfaces and MCP-enabled applications.

• Collaborate with software engineers and AI specialists to deliver robust, production-ready AI solutions.

• Participate in architectural discussions and contribute to the design and evolution of AI platforms.

• Investigate existing codebases, including partially documented legacy systems, and improve them through structured analysis and engineering best practices.

• Continuously experiment with new techniques, evaluate outcomes, and optimize AI systems for reliability, scalability, and maintainability.

• Communicate and defend technical decisions clearly, demonstrating ownership of implementation details and the ability to explain individual contributions in depth.

Requirements:

• Senior-level experience building and deploying production AI applications using Python and large language model technologies.

• Strong proficiency in Python, software engineering principles, and best practices for building maintainable production systems.

• Strong SQL skills and practical experience working with cloud data warehouses.

• Hands-on experience developing production-grade LLM and agentic AI applications.

• Demonstrated experience personally designing and building an MCP server, rather than only integrating with or consuming an existing server.

• Experience implementing tool calling, context management, multi-step orchestration, and agentic workflows.

• Practical experience integrating hosted LLM APIs, particularly Anthropic and OpenAI, into production applications.

• Strong knowledge of prompt engineering, prompt versioning, fallback mechanisms, and strategies for optimizing model cost, latency, and performance.

• Experience designing conversational AI solutions, intent classification and routing systems, or multi-API orchestration workflows.

• Experience developing LLM evaluation methodologies and frameworks to assess model quality and production behavior.

• Ability to analyze, understand, and work effectively within partially documented or brownfield codebases.

• A bachelor's degree in Computer Science, Software Engineering, Artificial Intelligence, Data Science, or a related field is preferred; equivalent professional experience is also acceptable.

• Strong analytical, problem-solving, collaboration, and communication skills.

• Professional English proficiency sufficient to participate in technical interviews, explain complex implementation details, and sustain in-depth technical discussions with precision.

• Nice to have: Experience deploying, fine-tuning, and evaluating open-source models using Hugging Face.

• Nice to have: Familiarity with GPU acceleration, model inference optimization, and performance tuning.

• Nice to have: Experience with MLOps practices, including CI/CD, observability, and reproducible pipelines.

• Nice to have: Experience with vector databases, Retrieval-Augmented Generation (RAG), and applied natural language processing (NLP).

• Nice to have: Experience building client-facing AI products and scalable AI-powered solutions.

Benefits:

• The position is based in Brazil; the specific work arrangement and remote-work eligibility are not specified in the original job description.

• Opportunity to work on production-grade LLM applications, agentic AI systems, and advanced conversational AI solutions.

• Significant technical autonomy and ownership of architectural and production design decisions.

• Collaboration with engineering professionals and AI specialists in a technology-focused environment.

• Opportunities to contribute to AI platform design and the development of scalable, AI-powered products.

• A learning-oriented environment that encourages experimentation, continuous improvement, and modern engineering practices.

• Salary, healthcare coverage, paid leave, bonuses, and other specific employment benefits are not specified in the original job description.

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