AI Architect II Google Solutions Line
J
JobgetherIT Services
Fully remote work flexibility within Canada.Full-TimeMiddle
Salary not disclosed
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Job Details
- Experience
- 4+ years of professional experience
- Required Skills
- GCPSoftware EngineeringLLMGenerative AI
Requirements
- 4+ years of professional experience in technical consulting, software development, cloud engineering, or a related technical discipline.
- 2+ years of experience designing, tuning, and implementing production-grade conversational AI, intelligent search, and customer experience solutions.
- Experience working with Gemini Enterprise for Customer Experience (GECX) or comparable enterprise AI platforms.
- Demonstrated experience building generative AI solutions using large language models, model fine-tuning, vector embeddings, and AI application frameworks.
- Experience developing retrieval augmented generation (RAG) and multimodal AI workloads on Google Cloud or similar cloud platforms.
- Hands-on experience using AI-assisted engineering tools such as GitHub Copilot, Claude Code, and Google Antigravity to accelerate software development.
- Strong understanding of cloud architecture principles, AI application design, and enterprise technology implementation.
- Ability to communicate complex technical concepts clearly to customers, engineers, and leadership stakeholders.
- Strong analytical thinking, problem-solving skills, and ability to manage multiple technical priorities.
- Excellent written and verbal communication skills with strong documentation capabilities.
Responsibilities
- Design and implement enterprise AI solutions across customer experience, commerce search, enterprise discovery, and agent-based automation use cases.
- Support full project delivery lifecycles, including discovery, architecture design, development, testing, deployment, and optimization.
- Provide senior-level technical guidance on conversational AI, intelligent search, cognitive solutions, and agentic automation.
- Collaborate with customer stakeholders, engineering teams, sales teams, and strategic partners to deliver successful professional service engagements.
- Lead solution design discussions, technical workshops, and architecture reviews with diverse audiences.
- Create comprehensive technical documentation, architecture diagrams, implementation plans, and solution recommendations.
- Develop AI-powered applications using large language models, vector embeddings, AI frameworks, retrieval augmented generation (RAG), and multimodal AI approaches.
- Build solutions leveraging Google Cloud technologies and support customers in maximizing cloud AI capabilities.
- Apply AI-assisted engineering practices using modern development tools to improve productivity, accelerate delivery, and enhance application development workflows.
- Stay informed on emerging AI trends and contribute to innovation initiatives, technical knowledge sharing, and continuous improvement.
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