Generative AI Architect- Day1 onsite in Orange, CT

Day 1 onsite in Orange, CT

Role: Generative AI Architect

Experienced AI Architect to join AI Center of Excellence and lead the AI use cases ideation, feasibility assessment, design and delivery of AI-driven solutions. T his role will be instrumental in helping business teams conceptualize disruptive AI use cases, evaluate their feasibility, define the technical and resource requirements needed for successful implementation, and deliver them . The AI Architect will work closely with data scientists, engineers, product owners, and business leaders to drive AI adoption, ensure scalability, and align AI initiatives with organizational goals.

The ideal candidate will possess deep expertise in AI architectures, cloud platforms (Azure), and machine learning, with a proven track record of originating and developing Gen AI solutions for real-world applications.

• Experience
• 8-10 years of experience in the ideation, design and end-to-end implementation of AI solutions.
• Proven track record of leading teams of AI engineers and reporting to senior leadership.
• At least 5 years of hands-on experience working with Azure AI, Azure OpenAI, Azure Cognitive Services, and Azure Machine Learning. Experience with AWS is a plus.
• Proven expertise in deploying Machine Learning models and AI applications in a cloud environment (Azure preferred).
• Technical Skills:
• Strong proficiency in Natural Language Processing (NLP) and deep learning techniques for building AI models.
• Experience with large language models (LLMs) such as GPT, BERT, and OpenAI's fine-tuned models.
• Knowledge of retrieval-based techniques, including semantic search, vector databases, and information retrieval systems.
• Familiarity with APIs and cloud-based data storage solutions (e.g., Azure Blob Storage, Cosmos DB, etc.).
• Experience with DevOps practices for machine learning, including CI/CD for AI systems, containerization (Docker), and orchestration (Kubernetes).

• Additional Skills:
• Solid understanding of cloud architecture, scalability, and security best practices in cloud computing.
• Experience in AWS cloud services is a strong advantage (e.g., AWS Lambda, S3, SageMaker).
• Familiarity with data pipeline technologies and distributed data processing frameworks (e.g., Spark, Hadoop) is a plus.
• Excellent problem-solving skills and the ability to work in fast-paced environments.

• Soft Skills:
• Strong communication and collaboration skills, with the ability to explain complex AI concepts to non-technical stakeholders.
• Leadership abilities to mentor teams and drive AI strategy in alignment with business goals.
• Ability to work independently and in team settings, balancing multiple priorities.