C2C Job opening for GCP Architect/Lead Data Engineer/Architect– AI & LLM Expertise @Ashburn, VA (Onsite

Location: Ashburn, VA (Onsite
Duration: 12 Months (Contract / Contract-to-Hire)
Experience: 15 Years

Job Summary:

We are seeking a highly skilled GCP Architect with deep expertise in Artificial Intelligence (AI) and Large Language Models (LLMs) to design and deliver next-generation AI solutions on Google Cloud Platform.
The ideal candidate will lead the architecture and implementation of scalable AI systems using Vertex AI, Generative AI frameworks, and LLM orchestration tools, ensuring high performance, security, and business alignment.

Key Responsibilities:

• Architect and implement AI/ML and Generative AI solutions on Google Cloud Platform (GCP).
• Design end-to-end GCP architectures including data ingestion, transformation, model training, deployment, and monitoring.
• Develop and fine-tune Large Language Models (LLMs) for enterprise-scale applications such as chatbots, summarization, and cognitive search.
• Integrate LLMs and Generative AI capabilities using Vertex AI, LangChain, and OpenAI APIs.
• Collaborate with data scientists, MLOps engineers, and business teams to translate business requirements into scalable GCP-based AI solutions.
• Ensure adherence to security, compliance, and cost optimization best practices within GCP.
• Define architectural standards, reusable frameworks, and reference implementations for AI and ML workloads.
• Support Cognizant client teams in implementing AI modernization initiatives and cloud transformations.

Required Skills & Experience:

• 10+ years of IT experience with at least 4–5 years in Google Cloud Architecture.
• Proven experience architecting solutions with GCP services such as Vertex AI, AI Platform, Dataflow, Pub/Sub, Cloud Functions, BigQuery, and Cloud Run.
• Strong understanding of LLM architectures (GPT, Gemini, LLaMA, Falcon, Claude, etc.) and Generative AI frameworks.
• Hands-on experience with Python, TensorFlow, PyTorch, and ML pipelines.
• Experience building or integrating RAG (Retrieval-Augmented Generation) and LangChain-based applications.
• Familiarity with MLOps, CI/CD, and Containerization (Docker, Kubernetes).
• Excellent problem-solving, design thinking, and stakeholder communication skills.

Preferred Qualifications:

• Google Cloud Professional Architect or Machine Learning Engineer Certification.
• Exposure to Generative AI governance, prompt engineering, and data privacy in AI systems.

Education:

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, Artificial Intelligence, or related field.

Regards,