Manager - AI Architect (AI Hub)

Skills	GTS Role	Mandatory Skills	Preferred Skills
AI Skills	AI Tech Lead (Architect)	Agentic Framework (Langgraph/Autogen/CrewAI)	Prometheus/Grafana/ELK Stack
		Machine Learning /Deep Learning Frameworks (TensorFlow/PyTorch/Keras)	Hugging Face Transformers
		Cloud computing platforms (AWS/Azure/Google Cloud Platform)	DevOps /MLOps /LLM Ops
		Docker, Kubernetes, DevOps tools like Jenkins and GitLab CI/CD.	Fine Tuning of LLMs or SLMs (PALM2, GPT4, LLAMA etc )
		Terraform or CloudFormation
		PostgreSQL/MongoDB/Cassandra
		RESTful APIs, GraphQL integrations
		RabbitMQ, Apache Kafka

Here are some of the key responsibilities of AI architect:  

. Team Management: You will be responsible for managing a team of AI and ML specialists, providing guidance, support, and mentoring to ensure their professional growth and development.

2. Project Management: You will oversee the planning, execution, and delivery of AI and ML projects, ensuring that they are completed within budget and timeline constraints. This includes defining project goals, allocating resources, and managing risks.

3. Strategy Development: You will collaborate with senior management to define the AI and ML strategy for the organization, identifying areas where AI and ML technologies can be applied to drive business growth and efficiency.

4. Technical Expertise: As a manager, you should have a deep understanding of AI and ML technologies, algorithms, and frameworks. You will provide technical guidance to your team, review their work, and ensure that the best practices and industry standards are followed.

5. Stakeholder Management: You will collaborate with various stakeholders, such as business leaders, product managers, and data scientists, to understand their requirements and translate them into AI and ML solutions. Effective communication and relationship-building skills are crucial for successful stakeholder management.

6. Talent Acquisition: You may be involved in the recruitment and hiring process, identifying and attracting top AI and ML talent to join your team. This includes conducting interviews, evaluating candidates' technical skills, and assessing their fit within the organization.

7. Continuous Learning: AI and ML technologies are rapidly evolving fields, and as a manager, you should stay updated with the latest advancements and industry trends. You should encourage continuous learning within your team and promote a culture of innovation and knowledge sharing.

8. Performance Evaluation: You will be responsible for evaluating the performance of your team members, providing constructive feedback, and identifying areas for improvement. You may also be involved in performance appraisals and career development discussions.

9. Collaboration and Cross-functional Coordination: AI and ML projects often require collaboration with other teams, such as data engineering, software development, and business analytics. You will need to coordinate with these teams to ensure smooth integration and deployment of AI and ML solutions.

10. Ethics and Compliance: AI and ML technologies raise ethical and legal considerations. As a manager, you should ensure that your team adheres to ethical guidelines and complies with relevant regulations, such as data privacy and security laws.

Overall, your role as a Gen AI and ML Specialist Manager is to lead and guide your team in leveraging AI and ML technologies to solve complex problems, drive innovation, and deliver value to the organization.

Educational qualifications

Work experience

Mandatory   technical & functional ski lls

Preferred technical & functional skills