About the role

AI summarised

We are seeking a Gemini Engineer with strong experience in building enterprise-grade Generative AI solutions leveraging Google Gemini models and the broader Google Cloud AI ecosystem. The role involves designing, developing, and deploying LLM-powered applications, integrating Gemini APIs into enterprise systems, and driving scalable AI adoption across business functions.

BusinessFull-timeOther Functions

Key Responsibilities

Lead end-to-end design and delivery of Gemini-powered AI solutions.
Architect scalable GenAI platforms on Google Cloud.
Drive AI solutioning workshops with business stakeholders.
Define reusable architecture patterns (RAG, agent-based workflows, orchestration).
Guide junior engineers on prompt engineering, evaluation, and optimization.
Establish governance standards for responsible AI deployment.
Manage small technical teams (2–5 engineers).
Support pre-sales, solution demos, and proposal development.

Requirements

Minimum 8 years of software engineering experience, including AI/ML exposure.
Proven experience designing cloud-native AI architectures.
Strong hands-on expertise with Gemini, Vertex AI, and LLM orchestration frameworks.
Experience implementing AI agents and workflow automation.
Strong understanding of data privacy, security, and AI risk management.
Experience leading small technical teams.
Google Cloud Professional certifications (preferred).
Experience integrating multimodal models (text + image + audio) (good to have).
Exposure to cost optimization strategies for LLM usage (good to have).