Gen AI Architect

Role: Gen AI Architect

Location: New Brunswick, New Jersey, USA

Work Arrangement: Hybrid / Onsite

Experience: 15+ Years

About The Opportunity

One of our clients, an AI-native start-up , is looking for an experienced Gen AI Architect with strong hands-on expertise in Generative AI, Large Language Models (LLMs), and Cloud-Native Architecture

The ideal candidate will have recently designed and developed LLM-powered solutions within a product development environment, translating business requirements into scalable, secure, and production-ready AI applications.

Key Responsibilities

• Design and architect scalable Generative AI and LLM-based solutions.
• Lead the development of AI-powered features and solutions within product engineering environments.
• Translate business requirements into effective AI/ML solutions.
• Evaluate, benchmark, and optimise LLMs for different business use cases.
• Lead technical proof of concepts (PoCs) and validate architectural feasibility.
• Collaborate with Data Scientists, ML Engineers, and Business Analysts to deliver AI solutions.
• Ensure solutions meet cloud-native architecture, performance, security, and scalability requirements.

Required Skills & Experience

• 15+ years of overall technology experience, with strong expertise in AI/ML and Generative AI.
• Recent hands-on experience building and deploying LLM-based solutions .
• Strong understanding of Transformer architectures and models such as BERT, RoBERTa, GPT, and Llama.
• Experience with Google Cloud Platform (GCP) and large-scale data processing.
• Proficiency in Python, TensorFlow/PyTorch, NumPy, Pandas, and Scikit-learn.
• Strong understanding of cloud-native architecture, APIs, microservices, and distributed systems.
• Experience with model evaluation, benchmarking, and performance optimisation.
• Knowledge of CI/CD, infrastructure automation, SQL/NoSQL databases, and cloud security.
• Experience with Python and C/C++ programming, including performance analysis and debugging.

Good to Have

• Experience with Vertex AI, Amazon SageMaker, Kubernetes, and Google Kubernetes Engine (GKE).
• Knowledge of data parallelism and model parallelism.
• Experience with enterprise AI strategy, data platforms, and data warehouse technologies.
• Exposure to GPU computing and CUDA.