Jobs at ScienceLogic

Positions 408

ScienceLogic is a leading provider of IT operations and monitoring solutions, delivering the SL1 platform that gives enterprises real‑time visibility across hybrid cloud, on‑prem, and edge environments. The company is recognized for its AI‑driven analytics and seamless integration with DevOps pipelines, helping large enterprises keep uptime and performance high.

ScienceLogic hires across a spectrum of technical roles—software engineering (frontend, backend, full stack), DevOps & SRE, data science, security engineering, and cloud architecture—as well as product management, UX, quality assurance, and technical support. Candidates can expect rigorous coding challenges, hands‑on cloud projects, and a culture that rewards innovation and collaboration.

By reviewing ScienceLogic listings on Job Transparency, applicants gain instant access to exact salary ranges, benefit details, and employee sentiment scores, allowing them to compare offers, negotiate confidently, and choose roles that match their career goals.

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Frequently Asked Questions

What is it like to work at ScienceLogic?
Employees describe a collaborative environment where cross‑functional teams tackle complex hybrid cloud challenges. The company emphasizes continuous learning, offering internal workshops on AI, cloud security, and advanced monitoring. Career paths often involve rapid progression from junior engineer to lead architect, supported by mentorship and regular performance reviews.
What types of positions are available at ScienceLogic?
ScienceLogic offers roles in software development (frontend, backend, full stack), DevOps & Site Reliability Engineering, data science, security engineering, cloud architecture, product management, UX design, quality assurance, and technical support. Positions are available in multiple locations, including Boston, San Francisco, and remote options.
How can I stand out as an applicant for ScienceLogic?
Tailor your resume to highlight experience with hybrid cloud or monitoring tools, and include metrics that demonstrate performance improvements. Contribute to open source projects related to observability or automate deployment pipelines. During interviews, prepare to solve algorithmic problems, discuss real‑world scalability challenges, and articulate how your work aligns with ScienceLogic’s focus on AI‑driven analytics.

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