Senior AI Engineer

Verity Group

. Design, develop, and evolve agents and workflows using MCP-based architectures .

Posted 9/18/2026full-timeRemote • BrazilSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in Python development and building intelligent workflows with generative AI models, focusing on scalable architectures and technical governance. Proficient in integrating APIs and ensuring observability through metrics and logging.

Highest-signal resume keywords

Python DevelopmentBuilding AgentsRAG PipelinesVertex AIDeepAgents

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Python DevelopmentBuilding AgentsRAG PipelinesVector DatabasesIntegrating APIsDeepAgentsVertex AIGemini ModelsObservabilityLLM Validation

Soft Skills

CollaborationSystems Thinking

Tools & Technologies

MCP-Based ArchitecturesDeepEvalLLM-as-a-Judge

Industry Keywords

Technical GovernanceEnterprise AI Agent PlatformsScalable ArchitecturesLLMOps PracticesTechnical Standardization

Tech Stack

Tools & technologies

Python

About the role

Key responsibilities & impact

Design, develop, and evolve agents and workflows using MCP-based architectures
Build RAG pipelines and context-retrieval mechanisms using vector databases
Integrate agents with APIs, tools, and external services to execute complex workflows
Develop agents in Python, preferably using Google ADK
Build and maintain agentic workflows using DeepAgents
Integrate AI models and services through Vertex AI and Gemini models
Define architectural standards, reusable components, and technical governance guidelines for the platform
Ensure solution observability through logs, metrics, and tracing
Partner with technical teams to ensure consistent integration between AI agents and enterprise applications
Design solutions aligned with business processes, integrations, and objectives
Ensure that developed components are scalable, reusable, and prepared for continuous evolution
Define and apply validation and evaluation strategies for LLMs and agents using metrics, DeepEval, and LLM-as-a-Judge

Requirements

What you’ll need

Strong experience with Python development
Hands-on experience building agents, intelligent workflows, and integrations with generative AI models
Experience with DeepAgents
Knowledge of MCP-based architectures
Experience with RAG pipelines and vector databases
Hands-on experience integrating APIs, tools, and external services
Experience with Vertex AI and Gemini models
Ability to define technical standards, reusable abstractions, and engineering best practices
Experience with observability, 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 collaborate effectively with engineering, architecture, and technical squad teams
Systems thinking to understand data flows, integrations, and enterprise environment constraints
Experience with enterprise AI agent platforms is a plus
Experience defining technical governance for AI-based solutions is a plus
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 evolution 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

Comp & perks

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