Educational Qualification* Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
Advanced degrees or certifications in AI, Machine Learning, or Data Science are highly desirable

Primary (Must have skills)* - To be Screened by TA Team: 1-2 years of experience in  architecting and designing  genAI solutions, chatbots and applications
1-2 years of experience in GenAI core skills like RAG pipelines, Langchain, and Agentic AI framework.
5-7 years of experience in Python.
1-2 years of experience with Azure AI services like AI search
2-5 years experience in API creation using FastAPI.

Role Description
The Gen AI Architect will be responsible for designing and implementing advanced AI solutions that drive innovation and efficiency within the organization. This role requires a deep understanding of AI technologies and the ability to translate business requirements into technical solutions.

Key Responsibilities
Working closely with the customer’s team to understand their perspective and propose solutions or approaches for the PoCs.
Making design decisions and ensuring the Solution/PoCs aligns with client needs.
Providing walkthroughs of the proposed Solution/PoCs design and obtain customer approval.
Documenting the understanding and conducting walkthroughs with the client team.
Creating scalable architectures and designs for GenAI projects
Proven track record as architect in designing and implementing AI solutions in a production environment.
Lead the design and development of GenAI Solutions, Chatbots and applications.
Collaborate with stakeholders to identify opportunities for AI-driven improvements.
Ensure the scalability and reliability of AI solutions.
Stay updated with the latest advancements in AI and machine learning.
Mentor and guide junior team members in AI best practices

Excellent problem-solving and analytical skills.
Strong communication and collaboration abilities.
Ability to work in a fast-paced, dynamic environment.
Leadership skills and experience managing cross-functional teams

Expected Outcome : Enhanced Efficiency: Streamline business processes and automate tasks to increase productivity.
Innovation: Drive the adoption of cutting-edge AI technologies to maintain a competitive edge.
Improved Customer Experience: Develop AI solutions that personalize and enhance customer interactions.
Data-Driven Insights: Extract valuable insights from data to inform strategic decisions.
Scalable AI Solutions: Ensure AI models are robust, scalable, and reliable.
Mentorship: Build a strong AI competency within the team through knowledge sharing and mentorship

Secondary Skills to be planned Post Hiring - Training Plan : Proficiency in Copilot Studio.
Strong understanding of deep learning algorithms and architectures.
Production grade AI solutions
Knowledge of data preprocessing, feature engineering, and model evaluation techniques.
Familiarity with natural language processing (NLP) techniques.
Understanding of AI ethics and bias mitigation strategies.
Knowledge of containerization and orchestration tools like Docker and Kubernetes.