Senior Artificial Intelligence Engineer – Agents

AM53 Smart Solutions

. Build and evolve the core architecture of the AI agent platform, ensuring standardization, governance, and high reusability .

Posted 10/3/2026full-timeSão Paulo • BrazilSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in AI agent platform architecture, focusing on standardization, governance, and reusability. Proficient in prompt engineering, distributed systems, and cloud environments, with a strong emphasis on collaboration and integration of AI initiatives.

Highest-signal resume keywords

Prompt Engineering TechniquesDistributed Systems ArchitectureAI Agents FrameworksCloud Environments (AWS, OCI)Software Development in Complex Environments

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Prompt EngineeringA/B TestingDistributed Systems DesignMachine Learning PlatformsAI Agent DevelopmentObservability ProtocolsEmbedding TechniquesVectorization TechniquesRAG TechniquesApplication Development

Soft Skills

CollaborationGovernanceEvaluation

Tools & Technologies

LangChainLlamaIndexSpring AIAWSOCI

Industry Keywords

AI Agent PlatformMetrics TrackingLoggingAuditingPrompt Security

Tech Stack

Tools & technologies

AWSCloud

About the role

Key responsibilities & impact

Build and evolve the core architecture of the AI agent platform, ensuring standardization, governance, and high reusability
Build and integrate robust mechanisms for tracking, metrics, evaluation, logging, observability, and auditing
Evaluate AI agent initiatives by understanding their needs, behavioral patterns, interactions, and orchestration requirements
Contribute to bringing critical components in-house, ensuring control, security, and consistency across the ecosystem
Collaborate with other AI initiatives, ensuring technical alignment and the sharing of lessons learned
Develop foundational MVPs, such as standardized documentation, agent templates, monitoring tools, and observability protocols

Requirements

What you’ll need

Knowledge of prompt engineering techniques (few-shot, self-ask, chain-of-thought, tree of thoughts)
Knowledge of A/B testing for prompts and model response evaluation
Knowledge of distributed systems architecture, with the ability to design and implement scalable, highly available solutions
Experience with application or machine learning platforms or pipelines
Hands-on experience with AI agents, orchestrators, or frameworks such as LangChain, LlamaIndex, Spring AI, or equivalent technologies
Proven experience in software development in highly complex environments
Experience with cloud environments (AWS, OCI)
Knowledge of embedding, vectorization, and RAG techniques
Familiarity with prompt security and prompt injection mitigation