• Lead the architecture, design, and development of firmware for wireless access points, setting technical direction and ensuring adherence to best practices. • Collaborate with cross-functional teams, including hardware, software, and product management, to define product requirements and develop long-term technology strategies. • Lead the resolution of complex technical challenges, including low-level debugging, performance optimization, and integration with advanced hardware components. • Drive the implementation and optimization of wireless networking protocols (e.g., 802.11 standards) and ensure robust security features, including encryption, authentication, and secure boot processes. • Identify and implement opportunities for innovation in firmware design, focusing on performance improvements, power efficiency, and scalability of wireless access point solutions. • Oversee the development and execution of rigorous testing and validation processes to ensure the highest levels of firmware quality and reliability. • Act as the primary technical liaison between the firmware team and other stakeholders, effectively communicating complex technical concepts to non-technical audiences. • Lead initiatives for continuous improvement of development processes, tools, and methodologies to enhance productivity and product quality.

• Contribute to the design and implementation of product features that align with technical strategy, quality standards, and functional requirements. • Develop full lifecycle code from development, testing, production, and subsequent fixes and improvements. • Participate in release planning, providing reliable estimations and delivering work that meets scope and quality expectations. • Engage in code reviews and other collaborative engineering practices. • Take part in daily standups, sprint ceremonies, and retrospective discussions. • Participate in security reviews of new development to help ensure compliance with Sophos security requirements and industry best practices. • Troubleshoot and resolve issues as a first responder in the team.

• Own Technical Direction and Architecture • Set the technical direction for AI systems - including shared AI SDKs, guardrails, evaluation frameworks, feedback systems, and agentic workflow infrastructure • Own architecture and technical strategy for complex backend and AI platform systems, from design through production • Lead technical design for ambiguous, cross-functional initiatives - evaluating tradeoffs, aligning stakeholders, and driving implementation • Evaluate and select technologies with a bias toward what ships well and scales sustainably • Build and Operate AI Systems • Write production code as a hands-on individual contributor - this is not a role that delegates implementation to others • Design and operate LLM-powered systems: RAG pipelines, agentic workflows, evaluation infrastructure, guardrails, and model observability • Own end-to-end reliability of AI systems from design through structured output delivery • Define quality benchmarks, evaluation frameworks, and feedback loops to continuously improve AI output accuracy and system reliability • Champion AI-Native Development • Champion and embed AI-native development practices and tools (e.g., Cursor, Augment) to achieve significant productivity gains across the team • Foster a culture of rapid iteration, high velocity, and quality - including guiding the effective use of AI code generation • Bring strong, informed opinions about how to get the most from AI-assisted development while maintaining reliability and correctness • Lead and Grow the Team • Mentor engineers, raise the quality of technical decision-making, and help the team execute with consistency • Establish coding standards, review practices, and architectural documentation that scale as the team grows • Help define what "good" looks like for a team building at speed without sacrificing quality • Partner with recruiting to build and grow the team • Collaborate Cross-Functionally • Work closely with engineering managers, product, design, and QA to translate requirements into executable technical plans • Participate actively in design reviews and roadmap discussions with grounded, implementation-level perspective • Handle most cross-team conflicts and technical decisions autonomously

• Design, build, and ship production-quality backend services, APIs, and AI platform components used across multiple engineering teams • Build and integrate LLM-powered systems such as RAG pipelines, AI SDKs, evaluation workflows, guardrails, prompt/tool orchestration, and model observability • Improve the reliability, scalability, observability, and operational quality of production AI systems • Build internal tools, frameworks, automation, and documentation that improve developer productivity and AI capabilities • Participate in code reviews, design reviews, debugging, incident response, and operational support • Contribute to technical design for complex projects, including evaluating tradeoffs and proposing pragmatic implementation plans • Partner with product, design, and engineering teams to translate platform needs into well-designed technical solutions • Help identify and reduce technical debt, reliability risks, and friction in the software development lifecycle • Collaborate with Staff and senior engineers to establish reusable patterns and raise engineering standards • Use agentic coding tools and LLM-assisted development as a primary part of your workflow — this is how the entire team operates • Critically evaluate AI-generated code for correctness, edge cases, and regressions — shipping quality output regardless of how it was produced • Contribute to the team's evolving practices around AI-accelerated development and testing