Expert Software Engineer (AWS)

Define and evolve system and data architectures, ensuring they meet performance, scalability, security, and cost‑efficiency targets.
Stay current with emerging backend technologies and trends, such as AI integration, edge computing, and new programming languages, to drive innovation.
Coach and mentor mid‑ and junior‑level developers; lead architecture and code reviews to uphold best practices.
Develop and maintain high- performance backend systems and APIs using modern technologies such as serverless architectures, microservices, and containerization.
Troubleshoot and resolve issues in production and development environments promptly and effectively to minimize downtime.
Collaborate closely with front- end engineers, devops, and product owners to deliver seamless, scalable solutions and align with business goals.
Deploy, monitor, and optimize backend services on AWS cloud infrastructure, ensuring high availability, performance, and cost- efficiency.

AWS Expertise: Hands‑on mastery of serverless (Lambda, API Gateway, Step Functions), container orchestration (ECS/EKS), and core services (EC2, S3, RDS, DynamoDB, SQS/Kinesis).
Languages & Frameworks
Infrastructure as Code: Proven experience with Terraform, CloudFormation, CDK or Serverless Framework.
Soft Skills: Excellent problem‑solving, communication, and interpersonal skills. Demonstrated ability to influence technical decisions and drive cross‑functional initiatives. Bonus: Experience with AI and machine learning integration. Experience with Customer Data Platforms (CDPs) or similar technologies, including data ingestion, segmentation, and real- time personalization use cases
Experience: 5+ years building and operating production backend services in AWS
CI/CD & DevOps: Strong background in end‑to‑end pipeline automation (GitHub Actions, Jenkins, CircleCI), artifact management, and blue/green or canary deployments.
Security & Compliance: Solid grasp of cloud security principles, threat modeling, encryption, and compliance frameworks.
Data Management: Deep understanding of SQL (PostgreSQL/MySQL) and NoSQL (DynamoDB, MongoDB) data modeling, indexing, and performance tuning.

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Cập nhật gần nhất lúc: 2025-11-14 21:45:03