AI Engineer – Generative AI, Agents

Azumo

. Build retrieval systems with chunking and embedding pipelines, hybrid search, reranking, and retrieval-quality evaluation .

Posted 9/22/2026full-timeRemote • Argentina, Dominican Republic, Mexico, Chile, Colombia, BrazilMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and deploying production AI systems with a focus on retrieval-augmented generation, containerized cloud solutions, and evaluation suite development. Proficient in modern backend programming, CI/CD practices, and effective communication in English.

Highest-signal resume keywords

Production Software DevelopmentLLM-Based Systems ExperienceCloud Deployment on Azure or AWSContainerization with DockerEvaluation Suite Design

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

PythonAsync ProgrammingAPI DesignTestingCode ReviewCI/CDRetrieval-Augmented GenerationModel-as-Judge ScoringRegression TrackingPrompt Design

Soft Skills

Clear Communication

Tools & Technologies

Azure AI SearchPgvectorPineconeQdrantFAISSLangGraphLangChainCrewAIDockerGitHub Actions

Certifications & Qualifications

Bachelor's Degree in Computer ScienceBachelor's Degree in Data Science

Industry Keywords

CI/CD PipelinesInfrastructure as CodeMCP ServersHuman-in-the-LoopLatency ManagementToken Cost AnalysisHigh-Throughput InferenceLLM SecuritySOC 2 ComplianceHIPAA Delivery

Tech Stack

Tools & technologies

AWSAzureCloudDockerPythonTerraform

About the role

Key responsibilities & impact

Build retrieval systems with chunking and embedding pipelines, hybrid search, reranking, and retrieval-quality evaluation
Develop stateful, multi-step agentic workflows with tool calling, MCP servers, structured output enforcement, context-window management, deterministic fallbacks, and human-in-the-loop gates
Create evaluation test sets, model-as-judge scoring, regression tracking, and error analyses
Implement prompt-injection defense, output validation, guardrails, PII handling, and graceful degradation
Deploy containerized systems on Azure or AWS with CI/CD and observability
Own latency, cost, token, and throughput budgets
Work inside client repositories and environments, including standups and occasional customer calls
Build production AI systems that are reliable, measurable, and affordable for real users

Requirements

What you’ll need

4+ years building and shipping production software, with a modern backend language (e.g., Python) as your primary focus
Experience with testing, code review, CI/CD, Git, containers, API design, and async programming
Production experience with LLM-based systems, including retrieval-augmented generation, function and tool calling, structured output enforcement, and prompt design
Hands-on experience with pgvector, Pinecone, Qdrant, FAISS, or Azure AI Search
Experience with LangGraph, LangChain, CrewAI, MCP, or native Python execution loops
Built an evaluation suite for an LLM system, including test-set design, model-as-judge or equivalent scoring, and regression tracking
Cloud deployment experience with Azure or AWS, Docker, CI/CD pipelines, and infrastructure as code such as GitHub Actions, Terraform, or Bicep
Ability to explain latency, token cost, and throughput trade-offs
Active use of Claude Code, Cursor, or GitHub Copilot in real delivery work
Clear written and spoken English, C1 or above
Bachelor's degree in Computer Science, Data Science, or a related field, or equivalent professional experience
Preferred: fine-tuning with LoRA, QLoRA, and PEFT; self-hosted/open-weight inference; multimodal systems; LLM security; SOC 2 or HIPAA delivery; streaming or high-throughput inference; open-source AI contributions or technical writing

Benefits

Comp & perks

100% remote-first culture (work anywhere in Latin America)
Paid time off (PTO)
U.S. Holidays
AI Training and certifications
Mentored career development
Profit sharing
$US remuneration