Senior Deployed AI Engineer (Gemini) (PCS848)

Hire Overseas; United States; On-site; USD 140,000 - 210,000; Full time

Benefits offered by this job

Paid time off

Remote work

Job summary

Remote Jobs is seeking 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 own components end to end—from frontend to data pipelines and deployment—working embedded with clients and ensuring production readiness on Google’s platform.

You’ll guide full‑stack development, data engineering, cloud infra, and client communications, mentoring juniors and contributing to internal

Qualifications

• 3–5 years of software or data engineering experience with hands-on AI tooling.
• Strong hands-on experience with Google AI stack (Gemini, Vertex AI) and production deployment on GCP.
• Proficiency in Python and TypeScript/JavaScript, with API design/consumption experience.
• Frontend experience in React and backend framework proficiency.
• Experience with RAG, embeddings, vector search, and agentic frameworks (ADK/LangGraph/LangChain).
• Strong GCP experience; AWS/Azure a plus.
• Professional English at a high level (C1/C2).
• Bachelor's or Master's in CS/Engineering or equivalent; Google Cloud certification a plus.

Responsibilities

• Develop user-facing interfaces in TypeScript and React, with backend services and APIs in Python or Node.
• Implement agentic behavior including orchestration, tool calling, memory, and guardrails.
• Build retrieval-augmented generation pipelines for ingestion, embeddings, and vector/hybrid search.
• Design and build agents with Gemini models, Vertex AI, ADK, and Agent Engine.
• Configure Gemini Enterprise for clients, including Agent Designer and agent sandboxes.
• Connect Gemini Enterprise to client landscapes via connectors with governance and auditability.
• Develop grounded, retrieval-backed apps with Vertex AI Search and BigQuery as data backbone.
• Maintain cost, latency, and quality through evaluation suites and regression tests.

Skills

TypeScript

React

Python

APIs

Cloud architectures

Data engineering

English fluency

Full-stack development

Education

Bachelor's or Master's in CS/Engineering

Tools

Gemini Enterprise

Vertex AI

Agent Development Kit (ADK)

LangChain

Terraform

CI/CD

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 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