Gen AI Architect

Job Description

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

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

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

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