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Principal Software Engineer
Not specifiedFull-timeSoftware ArchitectureEnterprise Software
Lead the architecture and hands-on development of a multi-tenant SaaS product operating across hybrid-cloud environments. Shape technical direction and guide engineers while building reliable, scalable systems that transform large datasets into actionable intelligence.
Responsibilities
- Design, develop, and deploy scalable microservices for distributed, data-intensive environments.
- Shape hybrid-cloud architecture and technical decisions across cloud, on-premises, data, security, and operations.
- Lead technical initiatives from discovery and design through implementation, production readiness, and ongoing evolution.
- Collaborate with product, architecture, engineering, DevOps, security, and customer-facing teams to develop technical solutions.
- Set technical direction, review designs, improve code quality, and strengthen maintainability, scalability, and reliability.
- Mentor engineers across teams and foster collaboration, ownership, and pragmatic decision-making.
- Remain hands-on with cloud-native technologies and select tools appropriate to the problem.
Requirements
- At least 10 years of experience, including technical leadership and hands-on design of complex distributed systems.
- Experience building large-scale distributed systems, microservices, and data-intensive production platforms.
- Experience developing cloud-native services on GCP, AWS, or Azure, including Kubernetes.
- Experience designing hybrid-cloud, multi-tenant SaaS systems with attention to scalability, tenant isolation, security, reliability, and operations.
- Experience with event-driven, high-throughput architectures using Apache Kafka, RabbitMQ, or similar technologies.
- Experience with relational databases, preferably PostgreSQL, as well as NoSQL and graph databases.
- Strong understanding of testing, observability, performance tuning, production readiness, and reliable engineering practices.
Nice to have
- Experience with Elasticsearch or similar search and analytics technologies.
- Familiarity with executing AI/ML workloads.