Cohesity is the leader in AI-powered data security. Over 13,600 enterprise customers, including over 85 of the Fortune 100 and nearly 70% of the Global 500, rely on Cohesity to strengthen their resilience while providing Gen AI insights into their vast amounts of data. Formed from the combination of Cohesity with Veritas’ enterprise data protection business, the company’s solutions secure and protect data on-premises, in the cloud, and at the edge. Backed by NVIDIA, IBM, HPE, Cisco, AWS, Google Cloud, and others, Cohesity is headquartered in Santa Clara, CA, with offices around the globe.
We’ve been named a Leader by multiple analyst firms and have been globally recognized for Innovation, Product Strength, and Simplicity in Design , and our culture.
Want to join the leader in AI-powered data security?
As an Performance Engineering Lead, you will architect and drive the development of generic, extensible infrastructure solutions for all datapath squads. Your primary focus will be to benchmark and analyze the performance of existing algorithms and systems, propose alternatives, and ensure the infrastructure is scalable, resilient, and adaptable to evolving needs.
HOW YOU'LL SPEND YOUR TIME HERE:
Lead the design and implementation of extensible benchmarking infrastructure for distributed systems, supporting multiple protocols and storage backends.
Collaborate with datapath squads to identify performance bottlenecks, optimize system throughput, and evaluate alternative algorithms and architectures.
Develop tools and frameworks for automated performance testing, profiling, and regression analysis across thousands of nodes.
Ensure infrastructure supports hyper-convergence, distributed data paths, and web-scale architectures, including NAS, object storage, and cloud services.
Drive consensus protocols, asynchronous programming, and performance optimization initiatives.
Represent operational issues to senior leadership, providing deep technical insights and actionable recommendations.
Mentor and coach engineers, fostering a culture of quality, ownership, and continuous improvement.
Minimum 10+ years of experience in infrastructure and back-end development, with a strong track record in large-scale distributed systems.
BS/MS/PhD in Computer Science or related field, with expertise in data structures, algorithms, and software design.
Expert-level programming and debugging skills in C, C++, Go. Expertise in — profiling, optimization, memory management, concurrency primitives (locks, atomics, thread pools, async I/O patterns) is an add-on
Deep understanding of system performance, scaling, multithreading, concurrency, and parallel processing.
Experience with NAS protocols (SMB, CIFS, NFS, S3), replication, disaster recovery, and distributed filesystems.
Proven ability to solve complex problems, debug production software, and drive tasks to completion.
Strong communication and analytical skills, with experience in technical feedback and code reviews.
Ability to build and lead successful technical teams, coaching and mentoring individuals.
Demonstrated experience leveraging AI tools to streamline workflows, enhance productivity, and support high-quality decision-making.
Preferred Skills
Minimum 3+ years focused on performance engineering, systems optimization, or infrastructure for data-intensive systems.
Experience with RocksDB or similar LSM-tree based storage engines — tuning, benchmarking, write amplification analysis.
Familiarity with Protocol Buffers and RPC frameworks — understanding RPC latency profiling, serialization overhead, and async call flow optimization.
Experience with Prometheus, Grafana, or similar observability stacks for performance monitoring and dashboarding.
Background in file system internals (VFS, FUSE, NFS/SMB protocols) or block storage systems.
Experience with Google Test / Google Benchmark frameworks for C++ micro benchmarking.
Familiarity with containerized or clustered test environments (Ansible, Jenkins, distributed test orchestration).
Experience with Python for performance analysis tooling, data visualization, or automation scripts.
Background in network performance — TCP tuning, RDMA, kernel bypass techniques.
Publications, talks, or recognized contributions in the performance engineering community.
Proven track record of building benchmark infrastructure and regression detection systems at scale — including statistical methods for detecting regressions (t-tests, change-point detection, noise filtering).
Familiarity with object storage, cloud services, and software-defined infrastructure.
Experience in benchmarking, profiling, and performance engineering for massively parallel and distributed data sets.
Knowledge of consensus protocols and fault-tolerance mechanisms.
Opportunities
Shape the technical trajectory of the company by delivering scalable, high-performance infrastructure.
Work on industry-leading hyperconverged platforms and limitless scale-out systems.
Collaborate across teams to deliver impactful solutions and drive quality via code reviews and operational excellence.
This role is ideal for a senior engineers who thrives in fast-paced, agile environments and is passionate about building robust, scalable infrastructure for benchmarking and performance optimization across diverse storage and data services
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Equal Employment Opportunity Employer (EEOE)
Cohesity is an Equal Employment Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, creed, religion, sex, sexual orientation, national origin or nationality, ancestry, age, disability, gender identity or expression, marital status, veteran status or any other category protected by law.
If you are an individual with a disability and require a reasonable accommodation to complete any part of the application process, or are limited in the ability or unable to access or use this online application process and need an alternative method for applying, you may contact us at 1-855-9COHESITY or [email protected] for assistance.
In-Office Expectations
Cohesity employees who are within a reasonable commute (e.g. within a forty-five (45) minute average travel time) work out of our core offices 2-3 days a week of their choosing.
Interested candidates based outside of the designated areas are welcome to apply, provided they have the right to work in the job location.
Skills Required
- 10+ years of experience in infrastructure and back-end development for large-scale distributed systems
- BS/MS/PhD in Computer Science or related field
- Expert-level programming and debugging skills in C, C++, Go
- Expertise in profiling, optimization, memory management, concurrency primitives (locks, atomics, thread pools, async I/O)
- Deep understanding of system performance, scaling, multithreading, concurrency, and parallel processing
- Experience with NAS protocols and storage backends (SMB, CIFS, NFS, S3), replication, disaster recovery, and distributed filesystems
- Proven ability to debug production software, solve complex problems, and drive tasks to completion
- Strong communication, analytical skills, technical feedback and code review experience
- Ability to build and lead technical teams, mentor and coach engineers
- Demonstrated experience leveraging AI tools to streamline workflows and support decision-making
- 3+ years focused on performance engineering, systems optimization, or infrastructure for data-intensive systems
- Experience with RocksDB or similar LSM-tree based storage engines
- Familiarity with Protocol Buffers and RPC frameworks and RPC latency profiling
- Experience with Prometheus, Grafana, or similar observability stacks
- Background in file system internals (VFS, FUSE, NFS/SMB) or block storage systems
- Experience with Google Test / Google Benchmark frameworks
- Familiarity with containerized or clustered test environments (Ansible, Jenkins)
- Experience with Python for performance analysis tooling, visualization, or automation
- Background in network performance (TCP tuning, RDMA, kernel bypass techniques)
- Experience building benchmark infrastructure and regression detection systems, including statistical methods (t-tests, change-point detection)
- Familiarity with object storage, cloud services, and software-defined infrastructure
- Knowledge of consensus protocols and fault-tolerance mechanisms
Cohesity Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Cohesity and has not been reviewed or approved by Cohesity.
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Wellbeing & Lifestyle Benefits — Leave and wellness programs appear broad, including flexible time off, company-wide refresh days, meeting-free focus blocks, an EAP, and learning/wellness perks such as MindGym sessions and Scribd access.
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Parental & Family Support — Parental and family benefits are positioned as a notable strength, with paid parental leave and additional family supports such as fertility benefits via Progyny.
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Healthcare Strength — Core coverage is described as comprehensive, with medical, dental, and vision offerings for employees and families alongside related support resources.
Cohesity Insights
What We Do
We believe that simplicity is the foundation of modern data management. Our mission is to radically simplify how organizations manage their data and unlock limitless value.
