Principal Software Engineer I at Perforce
Burlington, Massachusetts, USA -
Full Time


Start Date

Immediate

Expiry Date

04 Dec, 25

Salary

175000.0

Posted On

04 Sep, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Qt, Analytical Skills, Design Patterns, Jenkins, C++, Openmp, Mpi, Design, Test Driven Development, Session Management

Industry

Computer Software/Engineering

Description

Perforce is a community of collaborative experts, problem solvers, and possibility seekers who believe work should be both challenging and fun. We are proud to inspire creativity, foster belonging, support collaboration, and encourage wellness. At Perforce, you’ll work with and learn from some of the best and brightest in business. Before you know it, you’ll be in the middle of a rewarding career at a company headed in one direction: upward.
With a global footprint spanning more than 80 countries and including over 75% of the Fortune 100, Perforce Software, Inc. is trusted by the world’s leading brands to deliver solutions for the toughest challenges. The best run DevOps teams in the world choose Perforce.

POSITION SUMMARY:

We’re currently searching for a Principal Software Engineer to join the Team. The Principal Software Engineer will have extensive experience in software engineering with the ability to build robust, scalable, and high-performance solutions that meet the evolving needs of the business. They will design, modify, and develop software for the TotalView high-performance parallel debugger. Be part of a dedicated team building the latest HPC debugging and performance tools for demanding, massively parallel environments. The candidate will focus on core engineering tasks, including compiler and debugger-related development, while contributing to UI development as needed.

REQUIREMENTS:

  • Familiarity with software debuggers and how they work.
  • Ideally, will have been part of a team building the latest HPC debugging and performance tools for demanding massively parallel environments.
  • Design and develop new and advanced features in C++ on a variety of cross-platform Linux/UNIX/Mac OS X platforms.
  • 10+ years of industry-level experience with a proven track record of successful development.
  • 7+ years of C++ experience, including development using STL and C++ templates.
  • Experience in parallel/multi-process computing environments, especially HPC environments.
  • Knowledge of MPI and OpenMP parallel programming models, as well as compiler design and implementation.
  • Familiarity with ELF/DWARF object file formats and symbol tables.
  • Experience developing multi-threaded programs and working in different UNIX/Linux environments.
  • Familiarity with client/server architecture, including request/response protocols, session management, and data serialization techniques.
  • Experience developing user interfaces for desktop-based applications using Qt.
  • Demonstrated test-driven development and the ability to work and plan independently while sharing knowledge with others.
  • Strong problem-solving and analytical skills, with the ability to quickly understand and address complex technical challenges.
  • Excellent communication and collaboration skills, with the ability to effectively work within a cross-functional team
  • Knowledge of common C++ design patterns and the ability to use them when necessary
  • Agile/scrum development experience
  • Experience with Jenkins or other CI systems
Responsibilities
  • Design and develop new and advanced features in C++ on a variety of cross-platform Linux/UNIX/Mac OS X platforms.
  • Work on compiler and debugger-related tasks, including designing efficient workflows and algorithms for massively parallel environments.
  • Contribute to UI development using Qt and C++ to create efficient and user-friendly interfaces as needed.
  • Aid in efficient debugging, dynamic analysis, data collection, data reduction, and scalability for advanced parallel applications.
  • Design and develop efficient workflows and algorithms to work in massively parallel environments to aid in efficient debugging, dynamic analysis, data collection, data reduction, and scalability for today’s advanced parallel applications.
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