Senior Deployed AI Engineer – Gemini

🔥 0 minutes ago

🌐 Argentina, Peru, +1 more countries – Remote

🇦🇷 Argentina – Remote 🇵🇪 Peru – Remote 🇧🇷 Brazil – Remote

💵 $45k - $65k / year

⏰ Full Time

🟠 Senior

🤖 AI Engineer

👻 Ghost score 20%

What it means: the chance that no one is really hiring for this job.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Hire Overseas

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📋 Description

• 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 for clients, including Agent Designer, the Inbox for managing long-running agents, 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, grounding with Google Search, and BigQuery • Implement agent interoperability through the A2A protocol and MCP • Track Google's releases and translate new capabilities into client value • Write evaluation suites and regression tests for LLM-powered features • Monitor cost, latency, and quality in production • Deploy on GCP, Azure, or AWS • Build 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

• 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 the Google AI stack, including Gemini models and Vertex AI • At least one solution taken to production on GCP • Strong programming skills in Python and TypeScript or JavaScript • Experience building and consuming APIs • Experience with front-end development 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 is required within the first two months if not already held • Preferred certification: Google Cloud Professional Machine Learning Engineer • Experience with MCP servers, multi-agent patterns, or LLM evaluation tooling is nice to have • Experience with Terraform or CI/CD pipelines is nice to have • Experience with GCP, BigQuery, or Google Workspace integrations alongside Gemini Enterprise is nice to have • Availability during US business hours • 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 walking through one production AI system owned end to end • Portfolio and Loom video are both required to advance to the next hiring step

🏖️ Benefits

• Paid Time Off according to company policy • Holidays observed according to company guidelines • Compensation paid in USD • Paid bi-monthly on the 15th and 30th • Exam sponsorship and prep time provided for obtaining a Google Cloud certification • 100% remote setup • Dedicated full-time hours for team alignment and quality delivery

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