Develop and maintain high-performance backend systems and APIs using modern technologies such as serverless architectures, microservices, and containerization.
Define and evolve system and data architectures, ensuring they meet performance, scalability, security, and cost‐efficiency targets.
Deploy, monitor, and optimize backend services on AWS cloud infrastructure, ensuring high availability, performance, and cost-efficiency.
Collaborate closely with front-end engineers, devops, and
product owners to deliver seamless, scalable solutions and align with business goals.
Coach and mentor mid‐ and junior‐level
developers; lead architecture and code reviews to uphold best practices.
Troubleshoot and resolve issues in production and development environments promptly and effectively to minimize downtime.
Stay current with emerging backend technologies and trends, such as AI integration, edge computing, and new programming languages, to drive innovation.
Experience: 2+ years building and operating production backend services.
Languages & Frameworks
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).
Infrastructure as Code:Proven experience with Terraform, CloudFormation, CDK or Serverless Framework.
Data Management:Deep understanding of SQL (PostgreSQL/MySQL) and NoSQL (DynamoDB, MongoDB) data modeling, indexing, and performance tuning.
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.
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