Principal Software Engineer

Description

Curious about what it’s like to work at Cognyte?

At Cognyte, you’ll help build our Decision Intelligence product, bringing Nexyte capabilities to real-world impact.

You'll be part of building unique solutions shaped by real investigative methodologies, enabling customers to identify, investigate, visualize, and prevent criminal, terror, and security threats worldwide. Our solutions help organizations transform massive, diverse data into clear, actionable intelligence for a safer world.

We work with a startup mindset, moving fast, owning outcomes, and creating technology that helps make the world safer.

As a Cognyter you will:

• Design, develop, and deploy scalable microservices that handle and analyze massive amounts of data in distributed environments, with a strong focus on high availability, low latency, performance, resilience, and scalability.
• Shape the architecture of a hybrid-cloud, to build a multi-tenant SaaS product, influencing key technical decisions across cloud, on-prem, data, security, and operational domains.
• Lead complex technical initiatives end to end - from discovery and design through implementation, production readiness, and long-term evolution.
• Partner closely with Product, Architecture, Engineering, DevOps, Security, and customer-facing stakeholders to translate business needs into robust technical solutions.
• Drive engineering excellence by setting technical direction, reviewing designs, improving code quality, and raising the bar for maintainability, scalability, and reliability.
• Mentor and guide engineers across teams, helping them grow technically while fostering strong collaboration, ownership, and pragmatic decision-making.
• Stay hands-on with modern cloud-native technologies, while remaining open-minded and pragmatic in choosing the right tool for the problem.

Requirements

For that mission you'll need:

• At least 10+ years with proven technical leadership and hands-on experience leading the design of complex distributed systems.
• Strong experience designing and building large-scale distributed systems, microservices, and data-intensive platforms in production environments.
• Hands-on experience building cloud-native services in GCP/AWS/Azure environments using technologies such as Kubernetes.
• Proven Experience designing systems for hybrid-cloud, multi-tenant SaaS environments, including scalability, tenant isolation, security, reliability, and operational considerations.
• Experience with event-driven and high-throughput architectures using technologies such as Apache Kafka, RabbitMQ, or similar.
• Experience with both relational databases, preferably PostgreSQL, NoSQL databases such as MongoDB and Graph Databases.
• Experience with Elasticsearch or similar search and analytics technologies - an advantage.
• Strong understanding of testing methodologies, observability, performance tuning, production readiness, and engineering practices that support reliable, scalable systems.
• Familiarity with AI/ML workloads execution - an advantage.