New opportunity

AI / Agent Engineer

About the company

We are a young and fast-growing recruiting company with five years of experience working across Latin America and the United States. We partner closely with teams and founders to help them build strong, high-impact teams through recruitment, outsourcing, and team-building services. Our culture is built on effective communication, trust, and transparency. We believe great work happens when people feel heard, supported, and empowered to grow. Today, our team is made up of more than 80 professionals working across different projects throughout the region, collaborating remotely and learning from each other every day.

About the role

We are looking for a Senior AI / Agent Engineer to join an innovative technology team and help build and evolve the agentic layer of modern AI-powered applications. In this role, you will work hands-on with LLMs, MCP servers, tools, agentic workflows, RAG and Graph-RAG pipelines, transforming complex document and knowledge sources into reliable, grounded information that can be consumed by AI agents and multiple LLM providers. You'll collaborate closely with Product, Data, and QA teams to continuously improve answer quality, factual grounding, performance, and reliability. This is a highly technical role for someone who enjoys experimenting with rapidly evolving AI technologies while maintaining strong software engineering standards.

Responsibilities

• Build and evolve MCP servers, tools, and skills that expose application capabilities and knowledge to multiple LLMs
• Design and improve RAG and Graph-RAG pipelines that transform documents into structured, agent-friendly representations of facts, entities, and relationships
• Implement retrieval mechanisms across multiple layers, including source documents, vector-based retrieval, and graph-based retrieval
• Work with embeddings, vector databases, graph databases, and knowledge representations to improve retrieval quality and factual grounding
• Develop and optimize agentic workflows and integrations with multiple LLM providers such as Claude and Gemini
• Partner with QA to implement evaluation-driven improvements, measuring and improving answer quality, accuracy, and grounding
• Write clean, scalable, well-tested, production-grade Python code and participate in code reviews
• Monitor deployed agents and AI services, troubleshoot issues, and continuously improve performance and reliability
• Collaborate with Product, Data, QA, and other engineering disciplines in an agile environment
• Document architectures, prompts, agent behaviors, MCP interfaces, and technical decisions to ensure maintainability and knowledge transfer
• Stay current with emerging LLM, agentic AI, MCP, RAG, and AI engineering technologies and evaluate their potential application

Requirements

• 5+ years of professional software engineering experience, including at least 2+ years working with AI/ML or LLM-based applications
• Strong professional experience with Python and hands-on development of LLM-powered applications and agentic systems
• Direct experience building and integrating MCP servers, tools, or skills
• Solid experience with RAG architectures, Graph-RAG, embeddings, vector databases, and retrieval pipelines
• Experience working with graph data stores such as Neo4j, PostgreSQL, or Supabase-based graph implementations
• Experience integrating applications with multiple LLM providers, such as Claude, Gemini, OpenAI, or equivalent
• Strong software engineering fundamentals, including Git, automated testing, CI/CD, code reviews, and production-quality development practices
• Ability to design scalable and maintainable AI solutions, considering performance, reliability, security, and operational requirements
• Strong analytical and problem-solving skills, with the ability to work autonomously in ambiguous and rapidly changing environments
• Excellent communication and collaboration skills, particularly when working across Product, Data, QA, and Engineering teams
• Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience

Nice to have

• Previous experience working in technology consulting or client-facing environments
• Experience with AI evaluation frameworks, observability, and LLM monitoring
• Experience implementing temporal retrieval or replay mechanisms
• Experience with Life Sciences, Healthcare, or Pharmaceutical projects
• Experience working with cloud platforms and modern AI infrastructure
• Familiarity with additional agentic frameworks and orchestration technologies
• Experience designing AI solutions focused on enterprise knowledge management and document intelligence

Benefits

• People First culture
• Referral Program
• Free access to streaming platforms
• Free access to Spotify Premium
• GYM discount
• Travel discount
• E-Learning discount
• Birthday-day gift
• Points Program