Senior Deployed AI Engineer, Gemini

Hire Overseas

. Develop user-facing interfaces in TypeScript and React, with backend services and APIs in Python or Node .

Posted 10/2/2026full-timeRemote • Argentina, Peru, BrazilSenior💰 $45,000 - $65,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in developing user-facing interfaces using TypeScript and React, alongside backend services in Python or Node. Proficient in AI tools, LLM-based development, and deploying applications on GCP, with a strong focus on building retrieval-augmented generation pipelines and agentic frameworks.

Highest-signal resume keywords

TypeScript DevelopmentReact Front-End DevelopmentPython ProgrammingGemini Models and Vertex AIGCP Deployment

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

API DevelopmentData Pipeline MaintenanceRAG and Vector SearchAgentic FrameworksEmbeddings ImplementationSoftware EngineeringLLM-Based DevelopmentCloud DeploymentEvaluation Suite WritingRegression Testing

Soft Skills

CommunicationMentoringCollaboration

Tools & Technologies

Gemini EnterpriseClaude CodeGemini CLICodexCursorBigQueryAzureAWS

Certifications & Qualifications

Google Cloud Certification

Industry Keywords

AI SystemsAgent Development KitProduction DeploymentFull-Stack ProjectsProfessional English Proficiency

Tech Stack

Tools & technologies

AWSAzureBigQueryCloudGoogle Cloud PlatformJavaScriptNode.jsPythonReactTypeScript

About the role

Key responsibilities & impact

Develop user-facing interfaces in TypeScript and React, with backend services and APIs in Python or Node
Implement agentic behavior including orchestration, tool and function calling, memory, and guardrails
Build retrieval-augmented generation pipelines covering ingestion, chunking, embeddings, and vector and hybrid search
Design and build agents with Gemini models, Vertex AI, the Agent Development Kit, and Agent Engine
Implement and configure Gemini Enterprise, including Agent Designer, Inbox, and agent sandboxes
Connect Gemini Enterprise to client application landscapes through first-party and partner connectors with permissions, governance, and auditability
Build grounded, retrieval-backed applications with Vertex AI Search, RAG Engine, Google Search grounding, and BigQuery
Implement agent interoperability through A2A and MCP
Write evaluation suites and regression tests for LLM-powered features; monitor cost, latency, and quality in production
Deploy on GCP, Azure, or AWS and maintain data pipelines feeding AI systems
Use Claude Code, Gemini CLI, Codex, or Cursor daily with verification and review
Communicate progress, trade-offs, and blockers to clients and project leads
Support pre-sales when needed
Mentor junior engineers
Contribute to internal accelerators, reusable components, and engineering standards

Requirements

What you’ll need

3 to 5 years of software or data engineering experience
Extensive hands-on use of AI tools and LLM-based development over the past year
Strong hands-on experience with Gemini models, Vertex AI, and ideally Gemini Enterprise or ADK
At least one solution taken to production on GCP
Strong programming skills in Python and TypeScript or JavaScript
Experience building and consuming APIs
Front-end development experience in React or similar frameworks
Experience with at least one backend framework
Hands-on experience with RAG, embeddings, and vector search
Experience with at least one agentic framework such as Google ADK, LangGraph, or LangChain
Strong working experience with GCP; Azure or AWS is a plus
Fluency with Claude Code, Gemini CLI, Codex, or Cursor
Experience building and maintaining data pipelines
Professional English proficiency at C1 or C2 level minimum
Bachelor's or Master's degree in computer science, engineering, or a related field, or equivalent practical experience
Google Cloud certification required within the first two months if not already held
Updated resume
GitHub link or portfolio showing AI systems or full-stack projects built and shipped in production
1–2 minute Loom video introducing yourself and discussing a production AI system, evaluation, and reliability
Portfolio and Loom video required to proceed to the next hiring step

Benefits

Comp & perks

100% remote setup
Full-time schedule with dedicated hours
Paid bi-monthly on the 15th and 30th
Paid Time Off according to company policy
Holidays observed according to company guidelines
Google Cloud certification exam sponsorship and prep time provided
Compensation paid in USD