About Our ClientOur client is a general 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 RoleWe'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 will 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.ResponsibilitiesDevelop user-facing interfaces in TypeScript and React, along with the backend services and APIs behind them in Python or NodeImplement agentic behavior including orchestration, tool and function calling, memory, and guardrailsBuild retrieval-augmented generation pipelines covering ingestion, chunking, embeddings, and vector and hybrid searchDesign and build agents with Gemini models, Vertex AI, the Agent Development Kit, and Agent EngineImplement and configure Gemini Enterprise for clients, including Agent Designer, the Inbox for managing long-running agents, and agent sandboxesConnect Gemini Enterprise to client application landscapes through first-party and partner connectors with proper permissions, governance, and auditabilityBuild grounded, retrieval-backed applications with Vertex AI Search, RAG Engine, grounding with Google Search, and BigQuery as the data backboneImplement agent interoperability through the A2A protocol and MCP,



and track Google's releases closely to translate new capabilities into client valueWrite evaluation suites and regression tests for LLM-powered features, monitoring cost, latency, and quality in productionDeploy on cloud infrastructure across GCP, Azure, or AWS, and build and maintain the data pipelines feeding AI systemsUse agentic coding tools such as Claude Code, Gemini CLI, Codex, or Cursor daily with good judgment about verification and reviewCommunicate progress, trade-offs, and blockers clearly to clients and project leads, and support pre-sales when neededMentor junior engineers and contribute to internal accelerators, reusable components, and engineering standardsWhat We're Looking For3 to 5 years of software or data engineering experience, with extensive hands-on use of AI tools and LLM-based development over the past yearStrong 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 GCPExperience with front-end development in React or similar frameworks, and at least one backend frameworkHands-on experience with RAG, embeddings, and vector search, and with at least one agentic framework such as Google ADK, LangGraph, or LangChainStrong working experience with GCP; Azure or AWS is a plusFluency with agentic coding tools such as Claude Code, Gemini CLI, Codex, or Cursor, and experience building and maintaining data pipelinesProfessional English proficiency at C1 or C2 level minimum, as you'll work daily with international clients and colleaguesBachelor's or Master's degree in computer science, engineering, or a related field,



or equivalent practical experienceA 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 MLNice to HaveExperience with MCP servers, multi-agent patterns, or LLM evaluation tooling such as LangSmith, Langfuse, or promptfooExperience with Terraform or CI/CD pipelinesExperience with GCP, BigQuery, or Google Workspace integrations alongside Gemini EnterpriseWork Schedule100% remote setup so you can work wherever you're most productiveThis position operates on a full-time basis, with dedicated hours to ensure alignment with the team and delivery of quality workAvailability during US business hoursCompensation & Time OffCompensation paid in USDPaid bi-monthly on the 15th and 30thPaid Time Off according to company policyHolidays observed according to company guidelinesApplication RequirementsPlease submit:An updated resumeA 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 workA 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 buildOnly candidates who submit both a portfolio and Loom video will be moved to the next step of the hiring process.AgileEngine is an Inc. **** company that creates award-winning software for Fortune 500 brands and trailblazing startups across 17+ industries.
We rank among the leaders in areas like application development and AI/ML, and our people-first culture has earned us multiple Best Place to Work awards.WHY JOIN USIf you're looking for a place to grow, make an impact, and work with people who care, we'd love to meet you!
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📌 Senior Staff Ai Engineer — Enterprise Genai Architect (Remote) (Neuquén)
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📍 Neuquén