Data Architect - Generative AI

Key Responsibilities :

- Define and architect scalable solutions involving Generative AI, Retrieval-Augmented Generation (RAG), and LLMOps workflows.

- Lead the design and implementation of microservices-based, event-driven architectures leveraging REST APIs and API governance best practices.

- Collaborate with global teams and stakeholders to ensure architectural alignment and successful delivery of solutions to production.

- Provide strong technical leadership and mentorship to development teams.

- Hands-on development using Python frameworks such as Django, Flask, or FastAPI when required.

- Implement and optimize GenAI solutions utilizing Vertex AI, OpenAI, vector databases, and other LLM-based models.

- Leverage GCP technologies including Cloud Build, AutoML, Cloud Code, and foundational cloud services to build robust AI architectures.

- Apply Object-Oriented Analysis and Design (OOAD) principles in system design.

- Understand and integrate frontend technologies such as JavaScript and HTML5 when necessary.

- Quickly adapt to new tools, technologies, and evolving AI trends to drive innovation and improvement.

Mandatory Skills :

- Python programming and frameworks (Django, Flask, FastAPI)

- Vertex AI and Google Cloud Platform (GCP) fundamentals including Cloud Build, AutoML, and Cloud Code

- Generative AI, OpenAI, LLM-based models, and RAG workflows

- Experience with Vector Databases and search solutions

- Object-Oriented Analysis and Design (OOAD)

- Strong knowledge of microservices, event-driven architectures, REST APIs, and API governance

Preferred Skills :

- Azure cloud expertise (AZ-304 or AZ-305 certification is a plus)

- Hands-on experience with NoSQL databases such as Cosmos DB or MongoDB

- Excellent communication and collaboration skills, with experience working in global, cross-functional teams

- Strong problem-solving ability and a passion for mentoring teams