Senior Deployed AI Engineer (Gemini) (PCS848)

💼 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