Senior Deployed AI Engineer (Gemini) (PCS933)

Overseas; Buenos Aires; Remote; ARS 216,960,000 - 294,446,000; Full time

Job summary

Overseas is seeking a Senior Deployed AI Engineer to design, build, and deliver full-stack AI products for enterprise clients using Gemini and Google AI tooling. You will work embedded with clients and own front-end, backend, data pipelines, deployment, and evaluation.

Applicants should have 3–5 years in software/data engineering with hands-on AI tooling, strong Python/TS skills, and experience with RAG and vector search. Remote work and international collaboration are offered.

Qualifications

• 3–5 years software or data engineering with hands-on AI tooling
• Strong experience with Google AI stack (Gemini, Vertex AI) and production deployments
• Proficiency in Python and TypeScript/JavaScript; API design
• Frontend (React) and backend framework experience
• Familiarity with RAG, embeddings, vector search, and agent frameworks
• English proficiency for international collaboration
• Google Cloud certification is a plus and encouraged

Responsibilities

• Develop user-facing interfaces in TS/React and backend APIs in Python/Node
• Implement agentic behavior including orchestration, tool calling, memory, and guardrails
• Build retrieval-augmented generation pipelines with embeddings and vector search
• Design and build agents with Gemini models, Vertex AI, ADK, and Engine
• Implement Gemini Enterprise for clients and connect to client landscapes with governance
• Create grounded, retrieval-backed apps using Vertex AI Search and BigQuery
• Ensure agent interoperability via A2A protocol and MCP; monitor costs and latency
• Write evaluation suites and regression tests for LLM features in production
• Deploy on cloud (GCP/Azure/AWS) and maintain data pipelines
• Use Claude Code, Gemini CLI, Codex, Cursor with safety-focused reviews
• Communicate progress and blockers to clients and leads; assist pre-sales
• Mentor junior engineers and contribute to accelerators and standards

Skills

TypeScript

React

Python

Node.js

LLM Dev

Gemini

Vertex AI

GCP

English

Cloud deployment

Education

Bachelors or Masters CS/Engineering

Tools

Gemini Enterprise

Vertex AI

ADK

Gemini CLI

Codex

Job description

Senior Deployed AI Engineer (Gemini)

Peru, Argentina, Brazil

Remote

About Our Client

Our client is a global data and AI consulting firm serving enterprise clients across multiple industries, including FMCG, financial services, healthcare, manufacturing, and the public sector, with a team of data and AI experts spread across 20+ countries.

About the Role

We're looking for a Senior Deployed AI Engineer specialized in Gemini Enterprise and the Google AI stack to design, build, and deliver full-stack AI products for enterprise clients. You'll work embedded with clients, take AI features from idea to production, and serve as the team's reference for Google's enterprise AI platform.

You'll own your components end to end: the front end, the service behind it, the data and retrieval pipelines feeding it, the deployment, and the evaluations proving it works. Beyond Google platform depth, you'll be expected to deliver confidently across the full stack, including full-stack development, data engineering, cloud infrastructure, and client communication.

Responsibilities

• Develop user-facing interfaces in TypeScript and React, along with the backend services and APIs behind them 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 proper permissions, governance, and auditability
• Build grounded, retrieval-backed applications with Vertex AI Search, RAG Engine, grounding with Google Search, and BigQuery as the data backbone
• Implement agent interoperability through the A2A protocol and MCP, and track Google's releases closely to translate new capabilities into client value
• Write evaluation suites and regression tests for LLM-powered features, monitoring cost, latency, and quality in production
• Deploy on cloud infrastructure across GCP, Azure, or AWS, and build and maintain the data pipelines feeding AI systems
• Use agentic coding tools such as Claude Code, Gemini CLI, Codex, or Cursor daily with good judgment about verification and review
• Communicate progress, trade-offs, and blockers clearly to clients and project leads, and support pre-sales when needed
• Mentor junior engineers and contribute to internal accelerators, reusable components, and engineering standards

What We're Looking For

• 3 to 5 years of software or data engineering experience, with 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, Vertex AI, and ideally Gemini Enterprise or ADK, with at least one solution taken to production on GCP
• Strong programming skills in Python and TypeScript or JavaScript, with experience building and consuming APIs
• Experience with front-end development in React or similar frameworks, and at least one backend framework
• Hands-on experience with RAG, embeddings, and vector search, and 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 agentic coding tools such as Claude Code, Gemini CLI, Codex, or Cursor, and experience building and maintaining data pipelines
• Professional English proficiency at C1 or C2 level minimum, as you'll work daily with international clients and colleagues
• Bachelor's or Master's degree in computer science, engineering, or a related field, or equivalent practical experience
• A Google Cloud certification is a strong differentiator at application; if you don't hold one yet, obtaining one within the first two months is required, with exam sponsorship and prep time provided. The preferred certification is Google Cloud Professional Machine Learning Engineer, covering Vertex AI, generative AI, and production ML

Nice to Have

• Experience with MCP servers, multi-agent patterns, or LLM evaluation tooling such as LangSmith, Langfuse, or promptfoo
• Experience with Terraform or CI/CD pipelines
• Experience with GCP, BigQuery, or Google Workspace integrations alongside Gemini Enterprise

Work Schedule

• 100% remote setup so you can work wherever you're most productive
• This position operates on a full-time basis, with dedicated hours to ensure alignment with the team and delivery of quality work
• Availability during US business hours

Compensation & Time Off

• Compensation paid in USD
• Paid bi-monthly on the 15th and 30th
• Paid Time Off according to company policy
• Holidays observed according to company guidelines

Application Requirements

Please submit:

• An updated resume
• A GitHub link or portfolio showing AI systems or full-stack projects you’ve built and shipped in production, with a focus on the Google AI stack or agentic work
• A 1-2 minute Loom video introducing yourself, walking through one production AI system you owned end to end on the Google stack, and explaining how you approached evaluation and reliability alongside the feature build

Only candidates who submit both a portfolio and Loom video will be moved to the next step of the hiring process.