Staff Software Engineer
We are looking for an exceptional engineer to join our growing team at Nightfall. As a staff engineer, you’ll enable us to deliver our platform reliably, securely, and at massive scale. You’ll help architect low latency, real-time microservices that process & detect sensitive data at scale and will have opportunities for technical leadership.
This is a hybrid role based out of our San Francisco office.
The base salary range for this role is 180-220k.
Responsibilities
Oversee multiple cross-functional projects from conception to completion, ensuring alignment with business goals and customer needs.
Design and implement new features ensuring security, user experience, and scalability.
Advise on new technologies and guide architectural decisions to enhance system performance and reliability
Mentor junior team members and enforce best practices in a fast-paced environment.
Writing and maintaining documentation about internal and public services
Work effectively with other teams to support engineering programs and ensure seamless communication.
Participate in the team’s on-call rotation to ensure that product quality and performance SLAs are consistently met. Enhance processes and systems to continuously improve operations of the product.
Requirements
Minimum 7+ years of hands-on technical development experience
Experience programming in Go, C++, Java or related language
Experience with developing complex software systems scaling to substantial data volumes or millions of users with production quality deployment, monitoring and reliability.
Experience designing and building systems in a microservices-based architecture
Ability to decompose complex business problems and lead a team in solving them
A foundational understanding of multi-threaded programming, concurrency primitives, and data structures
BS/MS in Computer Science or a related technical field
Bonus Points
Experience working in high growth venture-backed startups
Blog, teach, mentor, or help others learn outside of your day to day responsibilities
Familiarity with AWS and managed infrastructure
Familiarity with Docker/Kubernetes
Experience with ML model deployments and inferencing is a plus
Average salary estimate
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