> Markdown version of [/jobs/ext/4402184-gen-ai-architect](https://www.wearedevelopers.com/jobs/ext/4402184-gen-ai-architect). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Gen AI Architect - **Company:** DIGITAL BUSINESS SOLUTIONS, INC. - **Location:** New Brunswick, NJ, United States - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Big Data, Cloud Computing Security, Cloud Engineering, Computer Programming, Continuous Integration, Data Warehousing, Software Debugging, Distributed Systems, Python (Programming Language), NoSQL, NumPy, Performance Tuning, Tensorflow, SQL Databases, Google Cloud, Pytorch, Large Language Models, Model Validation, Generative AI, Pandas, Scikit Learn, Kubernetes, Infrastructure Automation Frameworks, Transformer Architectures, Data Management, RoBERTa, GPT, Microservices - **Published:** October 15, 2026 - **Apply:** https://www.thejobnetwork.com/job/dfd35c26-adef-4066-998a-51dc6b7476ac/gen-ai-architect ## About the Role n \n * 15+ years of overall technology experience, with strong expertise in AI/ML and Generative AI. \n * Recent hands-on experience building and deploying LLM-based solutions. \n * Strong understanding of Transformer architectures and models such as BERT, RoBERTa, GPT, and Llama. \n * Experience with Google Cloud Platform (GCP) and large-scale data processing. \n * Proficiency in Python, TensorFlow/PyTorch, NumPy, Pandas, and Scikit-learn. \n * Strong understanding of cloud-native architecture, APIs, microservices, and distributed systems. \n * Experience with model evaluation, benchmarking, and performance optimisation. \n * Knowledge of CI/CD, infrastructure automation, SQL/NoSQL databases, and cloud security. \n * Experience with Python and C/C++ programming, including performance analysis and debugging. \n, * Experience with Vertex AI, Amazon SageMaker, Kubernetes, and Google Kubernetes Engine (GKE). \n * Knowledge of data parallelism and model parallelism. \n * Experience with enterprise AI strategy, data platforms, and data warehouse technologies.