Senior AI Engineer

This is a fully remote position, open to applicants in Brazil.

📋 Description

• Design, develop, and enhance agents and workflows utilizing MCP-based architectures

• Construct RAG pipelines and context-retrieval systems using vector databases

• Integrate agents with APIs, tools, and external services to implement intricate workflows

• Create agents in Python, ideally leveraging Google ADK

• Build and sustain agentic workflows with DeepAgents

• Incorporate AI models and services through Vertex AI and Gemini models

• Establish architectural standards, reusable components, and technical governance guidelines for the platform

• Ensure solution observability by implementing logs, metrics, and tracing

• Collaborate with technical teams to maintain consistent integration between AI agents and enterprise applications

• Design solutions that align with business processes, integrations, and objectives

• Guarantee that developed components are scalable, reusable, and primed for continuous evolution

• Define and implement validation and evaluation strategies for LLMs and agents utilizing metrics, DeepEval, and LLM-as-a-Judge

⛳️ Requirements

• Significant experience in Python development

• Practical experience in building agents, intelligent workflows, and integrations with generative AI models

• Familiarity with DeepAgents

• Understanding of MCP-based architectures

• Experience with RAG pipelines and vector databases

• Hands-on experience in integrating APIs, tools, and external services

• Experience with Vertex AI and Gemini models

• Capability to define technical standards, reusable abstractions, and engineering best practices

• Experience with observability practices, including logs, metrics, and tracing

• Knowledge of LLM and agent validation and evaluation, including tools such as DeepEval and LLM-as-a-Judge approaches

• Ability to work collaboratively with engineering, architecture, and technical squad teams

• Systems thinking to comprehend data flows, integrations, and constraints within the enterprise environment

• Experience with enterprise AI agent platforms is advantageous

• Experience in defining technical governance for AI-based solutions is beneficial

• Knowledge of scalable architectures focused on component reuse is a plus

• Experience in complex enterprise environments is a plus

• Previous involvement in technical standardization initiatives and the advancement of internal frameworks is a plus

• Knowledge of LLMOps practices, agent evaluation, and the continuous operation of AI solutions is a plus

• Experience with LLM and agent evaluation strategies and frameworks is a plus

🏝️ Benefits

• Meal voucher

• Food allowance

• Home office allowance

• Health insurance

• Dental insurance

• Life insurance

• Birthday day off

• Total Pass / Wellhub

• Boon Saúde app

• Discount partnerships

• Agreements with businesses and educational institutions

• Welcome kit

• Onboarding program

• Verity Learning

• Verity Break

• #VerityWithYou

• Access to professional development courses