Sr Back End Engineer

SaaS Analytics Startup

backend engineer

Posted 4 months ago

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LoopVOC is looking for a talented and motivated backend engineer who can hit the ground running and take our product to the next level. Our software is designed to revolutionize the way SaaS companies collect, analyze, and respond to feedback from their customers, by combining text analytics with a simple user experience. We're seeking someone to help us expand and scale our platform as an early partner in the engineering team. This position will have software and infrastructure responsibilities, from building new features and integrations to making fundamental architecture choices to optimizing machine learning and natural language processing.

We are an analytics startup. Data is at the heart of every decision we make, and you’ll be enabling our customers to use data in new and innovative ways. We are innately curious, radically transparent, and obsessed with feedback. We set aggressive goals and push ourselves to constantly evolve. We like to go after big ideas, fast… and are looking for someone that likes to do the same.

Our developers can live and work anywhere. We offer competitive salaries, unlimited vacation, and flexible hours. You’ll have the chance to earn equity in a fast-growing startup, work with cutting-edge technology, and build solutions for the top SaaS companies in the world. If you want to look back on your career and know that you were a vital part of building an awesome company, this role is for you.

Must Haves:

  • You’ve used Go, Java, C, or Python to create fast, maintainable production software.

  • You know what it takes to scale a SaaS application deployed in a cloud environment.

  • You embrace obstacles & are energized by new challenges with unproven solutions.

  • You’re a pro at designing and consuming RESTful APIs

  • You take ownership over project timelines & deliverables.

Extra Points:

  • You’ve worked in the B2B SaaS or analytics space.

  • You’ve built tools with machine learning and natural language processing.

  • You understand containerization of all your deployments in Docker and best practices for auto-scaling and load balancing your production environment in Kubernetes

  • You write automatic tests as a part of your development process and are part of a team that pushes code to production every day with tools for continuous integration and continuous deployment that you configure and administrate.

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