Principal AI Optimization Software Engineer Lead

Coding Provides technical leadership during code reviews for a solution/product area to assure it meets team standards, contains the correct test coverage, and is appropriate for the product or solution area. Brings expertise to code reviews to help improve code quality, proactively coaching and providing feedback to develop other engineers' skills. Ensures coding standards are followed. Screens for and establishes best practices in reviews and provides feedback on code to drive adherence to best practices. Uses automated source code analysis tools that are incorporated into the build/development process. Leads by example across teams and mentors others to produce extensible, maintainable, well-tested, secure, and performant code used across the company that adheres to design specifications. Leads efforts to continuously improve code performance, testability, maintainability, effectiveness, and cost, while accounting for and incorporating relevant trade-offs. Identifies best practices and coding patterns (e.g., leveraging state-of-the-art generative artificial intelligence [GenAI], approaches to source code organization, naming conventions) and provides deep expertise in the coding and validation strategy. Creates and applies metrics to drive code quality and stability, appropriate coding patterns, and best practices. Leads efforts to identify and anticipate blockers or unknowns during the development process, escalate them, and communicate how they will impact timelines, and then drives the identification and implementation of strategies and/or opportunities to address them. Acts as an expert on using debugging tools, tests, logs, telemetry, and other methods, and proactively leads verification of assumptions through while developing code before issues occur across products and teams in production. Leverages minimal telemetry data, triangulates issues, and resolves with minimal iterations. Leads incident retrospectives to identify root causes of problems, and owns the implementation of repair actions and the identification of mechanisms to prevent incident recurrence. Drives applying least-access principles, using logging, telemetry, and other appropriate mechanisms to investigate issues while retaining privacy and security, and champions those practices across the team. Establishes best practices and mentors others to create a clear test strategy that ensures solution quality, prevents regression from being introduced into existing code. Establishes best practices and mentors others on ensuring test plans incorporate security testing to validate security invariants (including negative cases). Provides technical leadership on adding new tests to cover gaps, deleting or fixing broken tests, and improving the speed, reliability, and defect localization of the overall test suite across a solution or product. Designs and executes plans for redesigning or rearchitecting difficult or untestable sections of code across solutions and/or products. Provides technical leadership to ensure system architecture and individual designs meet performance, scalability, resiliency, disaster recovery, cost of goods sold (COGS), and other requirements and expectations. Provides technical leadership for the identification of dependencies and incorporating them into the development of design documents for a product, application, service, or platform. Enables and fosters communications and proactively negotiates across teams to resolve conflicts around dependency ownership and required work. Develops substantial skills in tools inside and outside current areas of expertise. Collaborates with partner teams to ensure a set of products work well with the components of the partner team, ensuring proper end-to-end testing, live-site coverage, scalability, performance, and DRI escalation pathways are established before going live. Guides other members for project estimation and escalates only the most critical issues. Ensures solutions are scalable, financially responsible, and meet capture/storage guidelines. Provides technical leadership in efforts to classify, and analyze complex data and analyses on a range of metrics (e.g., health of the system, where bugs might be occurring), and sets expectations for outputs (e.g., notifications, dashboards) that improve monitoring and investigating security-related concerns and scenarios, system monitoring and/or issue identification and mitigation. Develops a playbook for the team to resolve issues. Coordinates people and resources to ensure DRI responsibilities are covered across teams. Implements and helps others implement solutions and mitigations to complex issues impacting the performance or functionality of live site services. Ensures playbooks are logical and understandable. Partners with and guides appropriate internal (e.g., product manager, privacy/security subject matter expert, technical lead) and external (e.g. customer escalation team, public forums) stakeholders and leverages expertise to anticipate, determine, and confirm customer/user requirements and their feasibility for one or more complex scenarios. Proactively seeks and leverages a variety of feedback channels to incorporate customer insights into future designs or solution fixes. Leads incorporation of unwritten requirements, such as appropriate continuous feedback loops that measure actionable, quantitative (e.g., customer value, usage patterns, solution performance) and qualitative (e.g., accessibility, globalization) indicators of value. Determines additional critical metrics. Understands and leads providing feedback on, and advocating for the security and privacy needs of the customer who will be using the complex set of solutions. --- Bachelor's Degree in Computer Science or related technical field 8+ years technical engineering experience with coding in languages C++, Python At least 2 years experience designing and implementing AI kernels, AI optimization algorithms, or AI compilation techniques Master's Degree in Computer Science or related technical field Deep expertise in one or more areas such as quantization, sparsity, speculative decoding, graph optimization, operator fusion, code generation, inference serving, batching and scheduling, caching.