Senior AI Engineer – Agentic AI & Enterprise Integration

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 50 professionals working across different projects throughout the region, collaborating remotely and learning from each other every day.

About the role

We are seeking a Senior AI Engineer to help design, build, and integrate production-ready Generative AI and agentic AI capabilities into an existing enterprise architecture. This role requires more than prompt engineering or experimentation. The engineer will be responsible for building Python-based services, connecting AI models to enterprise applications and data, developing retrieval-augmented generation solutions, and creating AI agents capable of completing multi-step workflows. The ideal candidate combines strong software engineering and systems integration experience with hands-on knowledge of LLMs, RAG architectures, Model Context Protocol, AI orchestration frameworks, embeddings, and vector databases.

Responsibilities

• Evaluate the current application and data architecture and determine how AI capabilities should be integrated
• Design and develop Python-based AI services, APIs, automation components, and backend integrations
• Build production-ready RAG pipelines, including document ingestion, chunking, embeddings, retrieval, reranking, and response generation
• Develop AI agents that can reason through tasks, call tools, retrieve information, maintain workflow state, and complete multi-step processes
• Use LangGraph, LangChain, or comparable orchestration frameworks to manage agent workflows
• Build and integrate MCP servers, MCP clients, APIs, and other tool-calling interfaces
• Integrate Claude and other enterprise LLMs into applications and business workflows
• Work with vector databases and semantic search technologies
• Connect AI services to existing Python, TypeScript, and Node.js applications
• Implement evaluation, logging, observability, retry handling, guardrails, and human approval processes
• Protect sensitive enterprise data through appropriate authentication, authorization, and data-access controls
• Partner with architects, application engineers, data teams, and business stakeholders to move AI use cases from concept into production.

Requirements

• Strong hands-on Python software engineering experience
• Experience developing backend services, APIs, integrations, or enterprise applications
• Production experience building applications that use LLMs or Generative AI models
• Hands-on experience designing and implementing RAG architectures
• Experience with document ingestion, chunking strategies, embeddings, semantic retrieval, and vector databases
• Experience building AI agents or multi-step AI workflows
• Experience with LangGraph, LangChain, or a comparable agent orchestration framework
• Understanding of Model Context Protocol and tool-based AI integrations
• Ability to integrate AI capabilities into an existing application architecture rather than only building standalone prototypes
• Experience evaluating AI output quality, reliability, latency, cost, and failure conditions
• Strong understanding of API design, authentication, data security, testing, and production support.

Nice to have

• Python, TypeScript and Node.js development experience.
• Experience with Anthropic Claude, the Claude API, Claude Code, or Claude Cowork.
• Experience creating or integrating MCP servers.
• Experience with multiple LLM providers or model-routing strategies.
• Experience with cloud-based AI services and infrastructure.
• Experience with event-driven architecture, asynchronous processing, queues, or background workers.
• Experience with Docker, Kubernetes, CI/CD, and production monitoring.
• Experience implementing human-in-the-loop review, agent permissions, and AI safety controls.

Benefits

• People First culture.
• Free access to streaming platforms.
• Free access to Spotify premium.
• GYM discount.
• Travel discount.
• E-Learning discount.
• Birthday-day