Senior Software Engineer: Scalable Systems & ML Pipelines

Logrocket; Boston, New York (MA, NY); On-site; USD 140,000 - 200,000; Full time

Benefits offered by this job

Health, Dental, Vision benefits

401k

Commuter benefits

Unlimited vacation

Generous stock options

Catered lunch and snacks

Team outings

Job summary

LogRocket is seeking an experienced software engineer to join our Boston-area team. You will help design and build systems that observe and replay user experiences at scale, enabling real-time search and bug detection across billions of logs. You will mentor peers and contribute to a culture of craftsmanship.

The role emphasizes reliability, cloud-native architectures, and collaboration with product and data teams to deliver high-impact features.

Qualifications

• 7+ years of experience in a full stack or backend development role, preferably with a SaaS company.
• Hands-on experience with highly available distributed systems.
• Experience with state-of-the-art cloud technologies and architectural principles.
• Familiarity with modern JavaScript-based applications and frameworks.
• Ability to work in scalable environments and collaborate across teams.
• Mentor junior engineers and contribute to team coaching.

Responsibilities

• Design a system to automatically detect the most common user paths across millions of events.
• Implement a search backend for real-time billions of log entries.
• Build a machine learning pipeline to detect bugs in customer apps.
• Automate database scaling to handle traffic spikes while controlling costs.
• Develop a system that recommends integrations based on customer toolsets.

Skills

7+ years experience

Full stack or backend

Cloud technologies

Distributed systems

JavaScript frameworks

Scalability/availability

Mentorship/leadership

Job description

LogRocket is seeking an experienced software engineer to join our Boston-area team. You will help design and build systems that observe and replay user experiences at scale, enabling real-time search and bug detection across billions of logs. You will mentor peers and contribute to a culture of craftsmanship.

The role emphasizes reliability, cloud-native architectures, and collaboration with product and data teams to deliver high-impact features.