Senior Deployed Ai Engineer (Gemini) (Pcs848)

Hire Overseas; São Paulo; Remote; BRL 699,000 - 998,000; Full time

Job summary

Hire Overseas is seeking a Senior Deployed AI Engineer to design, build, and deliver full‑stack AI products for enterprise clients. You will work embedded with clients, taking features from idea to production and serving as the reference on Google's enterprise AI platform.

You will own components end to end: frontend, backend, data pipelines, deployment, and evaluations. Expect full‑stack work across data engineering, cloud infrastructure, and client communication.

Qualifications

• Experience with AI tools and LLM-based development in the last year.
• Strong hands-on with Google AI stack including Gemini and Vertex AI.
• Frontend: React or similar; backend framework experience.
• Experience with RAG, embeddings, and vector search.
• Fluency in professional English (C1/C2).

Responsibilities

• Develop user interfaces in TypeScript/React and backend APIs in Python/Node.
• Implement agentic behavior including orchestration, memory, guardrails.
• Build retrieval-augmented generation pipelines.
• Design/build agents with Gemini models and Vertex AI.
• Configure Gemini Enterprise for clients and integrate with client landscapes.
• Connect to data landscapes with proper governance.
• Build grounded, retrieval-backed apps with Vertex AI Search and BigQuery.
• Write evaluation suites and monitor cost/latency in production.
• Deploy on GCP/Azure/AWS and manage data pipelines.
• Mentor engineers and contribute to reusable components.

Skills

Google AI stack

Gemini models

Vertex AI

ADK

React

Backend framework

RAG

Embeddings

Vector search

GCP

English (C1/C2)

Google Cloud Certification

Python

LangChain

Claude Code

Gemini CLI

Codex

Cursor

Education

Bachelor’s or Master’s degree in CS/Engineering

Tools

Gemini Enterprise

ADK

Gemini CLI

Claude Code

Codex

Cursor

LangGraph

LangChain

Job description

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
• 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