AI Architect

Role & responsibilities

Roles and Responsibilities

1. Solution Design and Architecture

• Architect and design scalable AI solutions that align with business objectives.
• Implement Generative AI models using frameworks like OpenAI, LangChain, TensorFlow, and PyTorch.
• Optimize AI models for performance, scalability, and reliability.

2. Technical Leadership

• Lead cross-functional teams in developing AI-driven applications.
• Mentor development teams on best practices in AI/ML technologies.

3. Stakeholder Collaboration

• Collaborate with business stakeholders to gather requirements and translate them into technical specifications.
• Present technical solutions and recommendations to leadership teams.

4. Innovation and Research

• Stay updated on advancements in AI/ML technologies, particularly Generative AI.
• Drive innovation by experimenting with new tools and techniques.

5. Project Management

• Oversee the end-to-end lifecycle of AI projects, ensuring timely delivery and quality standards.
• Develop detailed documentation for AI solutions, including architecture diagrams and user manuals.

6. MLOps Implementation

• Deploy AI solutions on cloud platforms (Azure/GCP) with best practices for MLOps.
• Monitor models for continuous improvement and ensure ethical use of AI.

Qualifications

• Technical Expertise:
• Proficiency in Generative/Agentic AI frameworks (e.g., OpenAI GPT, LangChain, Hugging Face).
• Strong programming skills in Python, TensorFlow, PyTorch.
• Experience with cloud platforms like Azure or Google Cloud for model deployment.
• Certifications:

- Relevant certifications in AI/ML or Solution Architecture are preferred.

• Benefits:

- Opportunity to work on cutting-edge AI projects.

- Collaborative work environment with growth opportunities.