Staff Software Engineer (Security)

Cohesity is a leader in AI-powered data security and management. Aided by an extensive ecosystem of partners, Cohesity makes it easy to secure, protect, manage, and get value from data — across the data center, edge, and cloud. Cohesity helps organizations defend against cybersecurity threats with comprehensive data security and management capabilities, including immutable backup snapshots, AI-based threat detection, monitoring for malicious behavior, and rapid recovery at scale.

We’ve been named a Leader by multiple analyst firms and have been globally recognized for Innovation, Product Strength, and Simplicity in Design.

Join us on our mission to shape the future of our industry.

We are looking for a seasoned, innovative  Staff Software Engineer to lead architecture, implementation, and end-to-end solution for our Security Products.

As part of our Security Engineering team, you will be responsible for architecture and end-to-end system design from inception through R&D, product delivery, customer show-case and deployment. You will develop multiple security products focused around Detection, Prevention, Remediation and Cyber Recovery from any security threats, applying Generative AI for various security solutions.

You will be focused on software delivered as a service in public/private/hybrid cloud environments. Additionally, you will be involved in designing, implementing, and delivering Multi-Cloud SaaS apps and software which will require knowledge of microservices, Kubernetes, caching, databases, message brokers, IAM, KMS, ETL, data/stream processing pipelines, CI/CD tools and cloud services like AWS, Azure, and GCP.

You will work in lock step with cross-BU platform, cloud SaaS engineering and infrastructure teams, enabling and delivering security products in the ecosystem with monthly release cycles.

You will also be working closely with the PM and UX teams to refine requirements and incorporate customer feedback. Communicating with cross functional stakeholders will be a regular part of the job. We’re looking for a technical lead who is motivated by technology and enjoys problem-solving, mentoring and collaborating with engineers across teams.

What You'll work on

1. Design and implement Microservices for highly available and scalable SaaS features for various security products.
2. Build and own frameworks for controlled releases and AB testing.
3. Diagnose and troubleshoot performance and availability issues pertaining to databases like Postgres, Elasticsearch and Mongodb and streaming data pipelines like Spark/Flink.
4. Perform exploratory analysis and POCs to identify performance and cost optimizations.
5. Monitor, optimize, and report on performance, throughput, and scalability trends.
6. Work with development teams to optimize data models and build optimizations to improve performance.
7. Work with operations to improve uptime, availability and performance.

 

Act as a technical lead to develop Cloud Security Products in distributed public/private cloud environments.

 

1. Lead initiatives and projects. Provide technical leadership and mentoring to team members.
2. Design and implement Cloud SaaS solutions.
3. Lead retrospectives and drive implementation of best practices.
4. Coordinate features and deliverables across multiple engineering and Product management teams to achieve project goals.
5. Collaborate with cloud operations to establish KPI for different services and own end to end delivery and lifecycle management.

 

Must have's

• B.S. or M.S. in Computer Science, Electrical Engineering or related experience.
• 10+ years of proven work experience in SaaS development.
• Experience in kubernetes-based microservices development.
• Experience working with cloud service providers such as AWS/Azure/GCP.
• Strong coding experience in these languages - C++, Golang.
• Experience in OLTP workloads - Postgres.
• Experience in NoSQL engines - MongoDB, ElasticSearch.
• Experience with Message brokers such as Kafka and Stream processing frameworks such as Spark/Flink.
• Experience with communication protocols such as REST and GRPC.
• Experience with Machine Learning models.
• Must be self-directed, organized, and detail-oriented as well as have the ability to multitask and work effectively in a fast-paced environ