Gen AI Architect

Job Title

Technical Expertise:
Strong programming skills in Java and familiarity with API-driven backend development. Experience with AI/ML frameworks like Tensor Flow, PyTorch, Hugging Face, or equivalent. Proficiency in building and deploying applications on Open Shift or other container orchestration platforms.

Generative AI

Experience:

Proven experience in designing and deploying generative AI solutions, including LLM-based applications. Understanding of prompt engineering, fine-tuning, and training generative models. System Design and Architecture:
Ability to design scalable, fault-tolerant, and secure AI systems. Knowledge of data governance, compliance, and model explainability in enterprise environments.

Cloud and Dev Ops:
Experience with CI/CD pipelines, containerization, and orchestration tools like Kubernetes. Familiarity with hybrid cloud and on-premises systems.

Soft Skills:

Strong problem-solving skills and a hands-on approach to tackling technical challenges. Excellent communication and collaboration skills to influence diverse technical and non-technical stakeholders.

Architectural Leadership:
Design and develop an end-to-end architecture for integrating generative AI capabilities into the current virtual assistant. Ensure solutions are model-agnostic, vendor-neutral, and adaptable across multiple platforms. Lead and mentor the technical team to implement and optimize the architecture.

Generative AI Integration:
Evaluate and select generative AI models and frameworks suitable for conversational AI enhancements. Build, fine-tune, and integrate generative models for tasks like response generation, summarization, and personalized interactions. Optimize performance, scalability, and accuracy for real-world use cases.

Platform Migration and Scalability:
Ensure seamless integration of backend APIs, maintaining high availability and performance. Develop a robust CI/CD pipeline for deploying and managing AI models and services on OCP.

Technical Implementation:
Stay hands-on with coding, prototyping, and testing AI components. Collaborate with cross-functional teams, including backend engineers, Dev Ops, and data scientists, to deliver integrated solutions. Build monitoring and alerting systems for AI model performance and application reliability.

Collaboration and Stakeholder Management:
Work closely with product managers, business stakeholders, and engineers to align technical solutions with business goals. Provide technical thought leadership, documentation, and knowledge-sharing to support team growth and alignment.

Experience working with virtual assistant platforms like Google Dialogflow or similar.

Knowledge of multiple generative AI models, including proprietary and open-source solutions.

Understanding of NLP, conversational AI, and related frameworks.