
GenAI Architect
4 weeks ago
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 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 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
(ref:hirist.tech)-
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