"Google Cloud Platform AI Architect" - New York, NY (Fully Onsite) - CG

Role: Google Cloud Platform AI Architect

Locations: New York, NY (Fully Onsite)

Duration: 12+ Months Contract

F2F Interview Highly Preferred - for Local Candidates.

Note: Candidate needs to be in the office 5 Days every week. Local or candidates from adjacent states only.

Job Description

• We are looking for an experienced Google Cloud Platform Architect to design and implement scalable, secure, and high-performance AI solutions on Google Cloud Platform.
• This role involves providing architectural leadership, reviewing technical designs, and guiding teams in building enterprise-grade AI applications leveraging Google Cloud Platform services.

Key Responsibilities

• Define and implement cloud architecture for AI/ML workloads on Google Cloud Platform.
• Review solution designs and ensure adherence to best practices for scalability, security, and performance.
• Architect and optimize enterprise AI applications, including LLM-based solutions in production environments.
• Design strategies for prompt engineering, RLHF, and RAG integration within Google Cloud Platform-based AI systems.
• Enable multi-modal AI capabilities (text, image, video, audio) using Google Cloud Platform services and frameworks.
• Collaborate on open-source AI initiatives or contribute to AI research publications.
• Implement A/B testing frameworks, personalization engines, and feedback-driven optimization pipelines.
• Oversee fine-tuning and deployment of LLMs using frameworks like Hugging Face, OpenAI, TensorFlow, and PyTorch, integrated with Vertex AI and other Google Cloud Platform services.

Required Qualifications

• Extensive experience in Google Cloud Platform architecture, including Vertex AI, BigQuery ML, Cloud Storage, and Kubernetes (GKE).
• Proven track record in enterprise AI solution design and production-level scaling of LLMs.
• Strong knowledge of prompt engineering, RLHF, and RAG techniques.
• Familiarity with multi-modal AI models and generative AI technologies.
• Contributions to open-source AI projects or published research in AI.
• Expertise in A/B testing, personalization, and feedback-driven optimization.
• Proficiency in AI frameworks and integration with Google Cloud Platform services.
• Data preparation & generation
• Cloud services - Google Cloud Platform