Solutions Architect- AWS, GenAI & ML

F2F Interview required

Boston, MA 4 days/week onsite Locals

Essential Functions and Responsibilities: Strategic Leadership

• Develop and articulate the AWS solution architecture strategy, ensuring alignment with business goals.
• Design and implementation of cloud-native solutions using AWS services, including serverless architectures.
• Drive architectural decisions for data-driven applications and AI/ML-enabled solutions.
• Implement AI/ML, GenAI, and cloud adoption across the enterprise.

AWS Solution Design

• Architect and deploy highly scalable, resilient, and secure solutions using AWS services:
• Compute: Lambda, EC2, ECS, EKS.
• Storage: S3, EBS, EFS, DynamoDB, RDS.
• Networking: VPC, API Gateway, CloudFront.
• Security: IAM, KMS, Cognito, WAF.
• DevOps: CloudFormation, Terraform, Code Pipeline, Code Deploy, Jenkins.
• Optimize cloud infrastructure for cost, performance, and reliability.
• Design the integration of on-premises systems with AWS cloud solutions.
• Implement serverless and microservices architectures leveraging AWS tools like AWS Lambda and API Gateway.
• Ensure compliance with cloud security best practices and AWS Well-Architected Framework principles.

GitHub Management and CI/CD Automation

• Oversee the organization of GitHub repositories, ensuring adherence to best practices for version control and collaboration.
• Design and implement CI/CD pipelines using GitHub Actions for automated testing, deployment, and monitoring.
• Establish branching strategies, enforce code quality standards through automated checks, and manage repository permissions to maintain security and integrity.
• Drive adoption of GitHub workflows for streamlined development and delivery processes.

Data Architecture

• Design and implement data pipelines, data lakes, and real-time data processing frameworks on AWS.
• Leverage AWS tools like Glue, Redshift, Kinesis, and Athena for data transformation and analytics.
• Establish data governance frameworks to ensure security and compliance.
• Collaborate with data scientists and engineers to operationalize AI/ML models.

AI/ML and Generative AI Integration

• Architect and deploy AI/ML solutions on AWS using SageMaker, Lambda, and related services.
• Implement Generative AI (GenAI) applications, such as large language models (LLMs), NLP, and computer vision.
• Optimize AI/ML workflows for scalability, performance, and cost on AWS cloud platforms.

Solution Design and Automation

• Review the design and development of Java, Java EE, Spring Boot, and Angular applications, ensuring integration with AWS services.
• Develop comprehensive architectural blueprints, including detailed AWS solution diagrams.

Leadership and Mentorship

• Participate in Architectural Review Board (ARB) in collaboration with the Chief Architect, ensuring enterprise-wide architectural alignment and governance.
• Build and mentor a team of architects, engineers, and data scientists, fostering a culture of innovation and excellence.
• Provide technical leadership throughout the project lifecycle, from inception to delivery.
• Partner with stakeholders to ensure solutions meet technical and business requirements.

Continuous Improvement

• Assess and enhance existing architectures, identifying opportunities to leverage AWS, AI/ML, and data technologies for modernization.
• Stay abreast of AWS advancements, AI/ML trends, and emerging cloud technologies.
• Conduct architectural reviews to ensure alignment with AWS best practices and enterprise standards.

Qualifications and Education: Education and Experience

• Bachelor s degree in Computer Science, Engineering, or a related field (Master s preferred).
• 15+ years of experience in technology architecture, with 7+ years designing AWS-based solutions.
• Proven experience leading enterprise-scale cloud transformation projects.

Technical Skills

• AWS Expertise:
• Compute: Lambda, EC2, ECS, EKS.
• Data: Redshift, DynamoDB, RDS, S3, Glue, Kinesis.
• Security: IAM, KMS, Cognito.
• Networking: API Gateway, VPC, CloudFront.
• DevOps: CloudFormation, Terraform, CodePipeline, Jenkins.
• Strong proficiency in Java, Java EE, Spring, Angular, and related frameworks.
• Expertise in AI/ML tools: TensorFlow, PyTorch, SageMaker.
• Proficiency in data architecture design, including ETL pipelines and data lakes.

Certifications

• Preferred:
• AWS Certified Solutions Architect (Professional).
• AWS Certified Machine Learning Specialty. (Optional)
• AI/ML certifications. (Optional)

Domain Knowledge

• Industry experience in Property & Casualty Insurance or other data-intensive sectors preferred.
• Familiarity with policy, claims, and billing systems preferred.