Senior Software Engineer, AI Intelligence Platform

About the Role:

This is a rare opportunity to be a key technical voice on Aura's AI Intelligence Platform, which unifies all of Aura's data and bridges the gap between AI agents and that data, with security and privacy as its foundational pillars. This platform is how we turn everything Aura knows about digital threats into timely, personalized insights that protect our customers and their families from harm, whether that's surfacing the one alert that actually matters, helping a parent understand a change in their child's online behavior, or spotting a scam before it lands.

As a Senior Software Engineer, you'll take on hard technical problems and own them end to end, building the infrastructure that lets AI operate over deeply sensitive information without compromising the security and privacy our customers trust us to hold. You'll work primarily in Python and TypeScript on AWS, on systems that serve millions of Aura customers.

This is a deeply technical, hands-on role. You'll take ownership of complex initiatives from architecture through production, and contribute to the technical direction a growing team of engineers builds on. We're looking for more than a strong coder: someone who brings order to ambiguous problems, sets a high standard for security and privacy engineering, and influences across teams through technical leadership.

What you'll do:

• Design, document, and drive the architecture for key platform components, ensuring scalability, reliability, security, and alignment with business goals.

• Own complex initiatives from design and architecture through development, deployment, and iteration, navigating ambiguous product goals and translating them into clear, scalable technical requirements.

• Build the foundation that unifies Aura's data into a trusted, high-quality source for generating intelligence.

• Architect how AI agents access and reason over sensitive data, designing for least-privilege access, strong isolation, and enforceable privacy guarantees so intelligence can be generated without ever crossing a data-safety boundary.

• Build the systems that turn that intelligence into personalized insights and actions that keep our customers and their families safe.

• Make and defend high-leverage technology choices across the stack, balancing scalability, cost, and operational simplicity.

• Champion engineering best practices for security, privacy, observability, testing, and operational excellence that the teams building on the platform adopt.

• Serve as a technical mentor, providing guidance on design challenges, performance tuning, and system reliability.

What you bring to the table:

• 5 - 8+ years of professional software engineering experience, with a track record of designing and shipping complex, large-scale distributed systems.

• Deep experience owning systems end-to-end on complex projects, from architecture through production operation.

• Strong knowledge of software design best practices, data structures, algorithms, and distributed-systems fundamentals.

• In-depth knowledge of cloud technology and the judgment to choose the right tool for the job, from serverless functions vs. containerized services to relational vs. NoSQL databases and the appropriate use of caches, queues, and data-processing pipelines.

• Demonstrated experience building systems that handle sensitive or regulated data, with security and privacy treated as first-class design constraints rather than afterthoughts.

• Exceptional communication and collaboration skills, with the ability to articulate complex technical concepts to both technical and non-technical stakeholders and to build alignment across teams.

• Demonstrated ability and desire to learn new technologies and to move quickly in a fast-evolving AI landscape.

• Bachelor's Degree in Computer Science or a related field, or equivalent work experience.

It would be great if you also had:

• Experience building AI/LLM-powered systems in production, such as agents, retrieval pipelines, evaluation, or LLM observability.

• A strong background in security, privacy engineering, or trust & safety.

• Experience with large-scale data platforms and data-intensive systems.

• Experience with AWS and Infrastructure as Code.