Senior Full Stack Developer

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IEBT Innovation

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2009

🤝 B2B

☁️ SaaS

🏢 Enterprise

B2B • SaaS • Enterprise

IEBT Innovation is a Brazilian innovation accelerator and consultancy that provides end-to-end innovation and digital transformation services to corporations, governments, universities and ecosystems. It operates the ZING platform for managing innovation hubs, challenges and entrepreneurship programs, runs acceleration programs, evaluates startups, and helps partners capture funding and build digital solutions. With a team of ~180 innovation and technology professionals, IEBT focuses on corporate innovation, public-sector projects, capacity-building and technology-enabled program delivery.

📋 Description

• Lead technical presales meetings (discovery/qualification) with mid-market and enterprise clients • Translate complex business needs into cloud architecture proposals (GCP) • Design and architect modern solutions using GCP's data and AI ecosystem • Ensure scalability, security, and cost optimization • Define technical project scope and estimate delivery effort • Prepare cloud consumption cost estimates (TCO and ROI) using the official Google Cloud calculator • Develop rapid prototypes, Proofs of Concept (PoCs), and AI/ML technical demonstrations • Validate solutions with technical and business decision-makers • Act as the technical arm of the commercial team in closing large deals • Respond to RFPs/RFIs • Represent IEBT in Google Cloud partner forums • Align offerings with Google Cloud programs and incentives

🎯 Requirements

• Experience or prior knowledge in client-facing roles such as Presales, Solutions Architect, Customer Engineer, or Cloud Technical Consultant • Strong hands-on experience with Google Cloud's data suite, especially BigQuery and Vertex AI • Experience with Generative AI services, Agent Builder, and AutoML • Knowledge of Python for data manipulation and usage of AI/ML SDKs/APIs on GCP • Practical familiarity with LLMs, prompt engineering, RAG (Grounded Generation) techniques, and vector databases native to or integrated with GCP • Knowledge in designing real-time or batch data pipelines • Knowledge of messaging bus systems, especially Pub/Sub • Basic understanding of MLOps, including Vertex AI Pipelines • Basic understanding of FinOps for cloud cost management and optimization • Basic knowledge of Terraform for provisioning AI/Data resources on GCP • Google Cloud Professional Machine Learning Engineer — desirable • Google Cloud Professional Data Engineer — desirable • Google Cloud Professional Cloud Architect — advantage • Experience in generative AI projects applied to corporate process automation, intelligent search, and customer service — advantage • Previous experience working in the official Google Cloud partner ecosystem — advantage