Later

Later

Later is a top social media management and influencer platform that simplifies visual content marketing for Instagram, Facebook, Twitter, and Pinterest. With over 2 million users globally, including renowned brands like Yelp and The Huffington Post, La...

Media
51-250
Founded 2014

Description

  • Design scalable, maintainable, and secure service architectures.
  • Identify and drive platform-wide improvements, new service development, and technical debt reduction.
  • Contribute to the long-term platform vision and engineering standards.
  • Build backend services using C# and TypeScript for web and background worker applications.
  • Design, containerize, and deploy services with Docker and Kubernetes.
  • Build and optimize cloud infrastructure on AWS or similar platforms.
  • Implement and maintain CI/CD pipelines, Git workflows, and Infrastructure as Code.
  • Apply security best practices across applications and infrastructure.
  • Improve reliability and scalability through test automation, performance profiling, and optimization.
  • Integrate and manage third-party APIs and explore AI/ML-driven features.
  • Serve as a technical mentor for junior engineers and peers.
  • Collaborate with Product Managers, Staff Engineers, and cross-functional teams to define requirements and deliver platform solutions.

Requirements

  • Proficiency with C# and TypeScript for backend services.
  • Strong experience with SQL and NoSQL databases; PostgreSQL expertise preferred.
  • Expertise in system architecture for secure, scalable, and maintainable platforms.
  • Broad experience with Docker, Kubernetes, and AWS or equivalent cloud platforms.
  • Strong knowledge of DevOps practices, including Git, CI/CD, and Infrastructure as Code.
  • Expertise in application and infrastructure security best practices.
  • Strong understanding of testing and automation practices.
  • Experience with performance optimization for reliability and scalability.
  • Proficiency in third-party API integration and management.
  • Experience or strong interest in AI/ML applications in production systems.
  • Demonstrated mentorship ability and experience working in ambiguous, complex problem spaces.

Benefits

  • US salary range of $180,000–$230,000.
  • Market-based, data-driven compensation with biannual reviews.
  • Permanent team members are eligible to participate in various benefits plans.
  • Fully remote options are available for select positions.
  • Office locations in Boston, Vancouver (BC), Chicago, and Vancouver (WA).

Interested in this position?

Apply directly on the company website

Apply Now

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