Job Details

Job Description:

Responsibilities:

• rchitect and design AI/ML solutions that leverage AWS services and a variety of GenAI and ML models to meet critical business needs.
• Collaborate with Data Scientists and Machine Learning Engineers to create a robust conceptual, logical and practical solution architecture that supports the deployment and scaling of AI models.
• Develop technical roadmaps that align with product roadmaps
• Ensure that AI solutions comply with data privacy and security protocols while integrating smoothly with legacy systems.
• Build solution architecture that optimize the performance of AI systems by leveraging AWS's scalable environment and manage resource allocation to maximize efficiency.
• Provide architecture guidance in AWS AI services such as SageMaker, Lambda, Bedrock, Llama and other AWS Machine Learning models to streamline development and deployment processes.
• Support training and development efforts to enhance the team's understanding and use of AWS cloud solutions in AI projects.
• Evaluate new technologies and AWS updates to continuously improve and expand AI capabilities within the company.
• Co-develop and drive the AI/ML strategy, ensuring alignment with enterprise capability maturity and progression.
• Provide thought leadership in enterprise AI/ML architecture, ensuring scalability, resilience, and alignment with organizational goals.
• dhere and implement architecture governance frameworks to ensure best practices and consistency across AI/ML initiatives.
• pply principles of Responsible AI to ensure ethical and transparent AI development and deployment.
• Evaluate and recommend market-leading tools and technologies, such as TensorFlow, PyTorch, Hugging Face, Databricks, and in-house platforms, to enhance AI/ML capabilities.
• Foster collaboration across teams, ensuring influence and alignment in cross-functional AI/ML initiatives.

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
• Extensive experience with AWS cloud services, particularly those related to AI and ML like AWS SageMaker, Lambda, and EC2.
• Proven track record in designing and deploying AI/ML architectures and solutions in a large-scale environment.
• Strong understanding of machine learning algorithms and AI implementation challenges.
• Experience with software development life cycle (SDLC) and agile methodologies.
• Demonstrated expertise in strategic planning and enterprise AI/ML capability development.
• Strong financial acumen to manage AI/ML investments and ensure cost-effective implementation.

• WS Certified Machine Learning Specialty or AWS Certified Solutions Architect certification.
• Strong leadership skills with the ability to manage cross-functional teams.
• Excellent problem-solving, organizational, and analytical abilities.
• Effective communication skills to articulate complex technical ideas to non-technical stakeholders.
• Experience with enterprise architecture tools such as TOGAF, ArchiMate, or similar frameworks.
• Proficiency in Kubernetes, Docker, and data pipeline tools such as Apache Kafka and Airflow.