Fyntera IT Services
Essential Functions and Responsibilities
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
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.
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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
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.
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