Senior Backend Engineer

About the role

Join our team to build the backend systems that drive our AI-integrated physical security platform. You will design infrastructure that connects cloud services with a global network of cameras and sensors to enable real-time threat detection and automated response. In this capacity, you will own the core services that process, route, and secure high-volume telemetry from edge devices worldwide. You will partner closely with data scientists and product teams to translate AI requirements into robust backend primitives. The work involves creating scalable event loops that react to complex inputs from video, audio, and structured sensor signals. You will be responsible for ensuring that safety-critical workflows meet stringent standards for correctness and performance. This role demands collaboration across engineering, security, and operations to maintain a cohesive user experience. You will contribute to the architectural vision that defines how intelligent features scale globally.

Key facts

What you'll do

• Architect distributed systems for AI-powered monitoring and automated workflows, ensuring components operate reliably under load.
• Build high-throughput pipelines to ingest and process massive volumes of sensor, video, and audio data from thousands of endpoints.
• Create event-driven logic to trigger alerts, verification routines, and dispatch actions while preserving data integrity.
• Develop infrastructure to deploy and integrate large audio and video models into production, managing the lifecycle of AI artifacts.
• Prototype new AI features and move them into production environments, iterating from experimental code to hardened services.
• Optimize system reliability, availability, and latency across both edge and cloud components to meet strict operational targets.
• Collaborate with cross-functional teams to deliver end-to-end safety solutions that align with customer needs and regulatory expectations.
• Define standards for testing, observability, and continuous deployment to support rapid yet safe delivery of backend capabilities.
• Design storage strategies for time-series video and metadata that balance cost, query performance, and retention policies.
• Implement secure communication protocols between devices and the cloud, ensuring that sensitive data is handled appropriately.
• Investigate and resolve complex production incidents, coordinating with SRE and support teams to restore service quickly.
• Mentor junior engineers by providing code reviews, technical guidance, and clear documentation of backend patterns.
• Evaluate new technologies and frameworks to determine their suitability for integration into the core platform.
• Maintain a deep understanding of the threat landscape to ensure that backend controls mitigate identified risks.

Requirements

• 5+ years of experience in backend engineering for production-scale systems, with a focus on high-availability services.
• Proven ability to design event-driven architectures and distributed systems that handle asynchronous workflows and failure modes.
• Experience developing data-intensive or AI-integrated applications that manage large datasets and complex model inputs.
• Background in high-throughput, real-time data processing, including streaming architectures and low-latency pipelines.
• Strong programming skills in languages such as Go or Python, with a demonstrated ability to write efficient and maintainable code.
• Experience with modern cloud infrastructure, including container orchestration, service discovery, and infrastructure as code.
• Ability to iterate quickly in ambiguous environments, making informed decisions with incomplete information and evolving requirements.
• Ownership mindset for delivering end-to-end production systems, from initial design through deployment, monitoring, and iteration.
• Understanding of distributed systems concepts such as consensus, replication, partitioning, and idempotent operations.
• Familiarity with security best practices for backend services, including authentication, authorization, and audit logging.
• Comfort working with relational and time-series databases, as well as caching layers to support high-performance access patterns.
• Willingness to participate in on-call rotations and respond to production issues outside standard business hours.
• Excellent written and verbal communication skills to coordinate with technical and non-technical stakeholders.

Nice to have

• Familiarity with deploying machine learning models in multimodal, video, or audio domains, including model serving and inference optimization.

Practical notes

• Visa sponsorship is available and the company will make reasonable efforts to secure visas for successful candidates.
• Benefits include 100% premium coverage for employees on at least one healthcare plan (80% for family), HSA/FSA options, mental health support, parental leave, fertility benefits, professional development stipends, and daily lunches.
• Compensation includes base salary and may include RSUs.
• This role is based in San Mateo, California, United States, and requires physical presence in the office.
• Employment is full-time, and candidates must be eligible to work in the United States without requiring immediate work authorization sponsorship.
• The company may conduct background checks as part of the hiring process, consistent with applicable laws.
• Relocation assistance is not specified and should be discussed with the recruiting team during the interview process.
• The listed benefits and compensation details are subject to change based on internal policies and regulatory requirements.