Senior Deployed AI Engineer (Gemini)
New
H
Hire OverseasAI consulting
Peru, Argentina, Brazil, Availability during US business hoursFull-TimeSenior
Salary not disclosed
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Job Details
- Languages
- Professional English proficiency at C1 or C2 level minimum
- Experience
- 3 to 5 years of software or data engineering experience
- Required Skills
- PythonGCPTypeScriptReact
Requirements
- Have 3 to 5 years of software or data engineering experience and extensive hands-on use of AI tools and LLM-based development over the past year.
- Have hands-on experience with Gemini models and Vertex AI, ideally Gemini Enterprise or ADK, including at least one solution taken to production on GCP.
- Have strong programming skills in Python and TypeScript or JavaScript, with experience building and consuming APIs.
- Have front-end experience with React or a similar framework and experience with at least one backend framework.
- Have hands-on experience with RAG, embeddings, and vector search, and at least one agentic framework such as Google ADK, LangGraph, or LangChain.
- Have strong working experience with GCP; Azure or AWS experience is a plus.
- Be fluent with agentic coding tools such as Claude Code, Gemini CLI, Codex, or Cursor, and have experience building and maintaining data pipelines.
- Have professional English proficiency at C1 or C2 level minimum.
- Have a bachelor's or master's degree in computer science, engineering, or a related field, or equivalent practical experience.
- Hold a Google Cloud certification or obtain one within the first two months; the preferred certification is Google Cloud Professional Machine Learning Engineer.
- Be available during US business hours.
Responsibilities
- Develop user-facing interfaces in TypeScript and React, plus 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 for ingestion, chunking, embeddings, and vector and hybrid search.
- Design and build agents with Gemini models, Vertex AI, the Agent Development Kit, and Agent Engine.
- Configure Gemini Enterprise for clients and connect it to client applications with appropriate permissions, governance, and auditability.
- Build retrieval-backed applications using Vertex AI Search, RAG Engine, Google Search grounding, and BigQuery.
- Write evaluation suites and regression tests, and monitor production cost, latency, and quality.
- Deploy on GCP, Azure, or AWS and build and maintain data pipelines feeding AI systems.
- Communicate progress, trade-offs, and blockers to clients and project leads, and support pre-sales when needed.
- Mentor junior engineers and contribute to internal accelerators, reusable components, and engineering standards.
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