Solution Architect

Description:

We are seeking an experienced solution Architect to support various GenAI and Machine learning projects.

This role is pivotal in designing and implementing advanced AI solutions within our AWS-powered infrastructure.

The AI/ML solution Architect will be responsible for creating robust overall end to end solutions for GenAI projects that integrate seamlessly with our existing IT framework and support our ambitious goals for technological innovation and efficiency.

This position is ideal for someone passionate about harnessing the power of AI technologies and building end to end solutions to drive significant business impact.

Responsibilities:

Architect 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.

Adhere and implement architecture governance frameworks to ensure best practices and consistency across AI/ML initiatives.

Apply 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.

Qualifications:

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.

Desired Skills:

AWS 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.

Must have Skills

Gen AI and machine Learning.

Java, Spring Boot is required.

Inadept knowledge in sage maker, Lambda, Bedrock, AWS Machine learning.

3-5 years of experience in AWS EC2 is required.

Certification in AWS will help.