Senior Software Engineer - AI Experiences, Monetization

Microsoft•New York, NY

2d•Hybrid

About The Position

The Senior Software Engineer will work on Microsoft AI Experiences’ Monetization Demand Quality team, which builds services that protect advertising quality and make creative review fast, accurate, and reliable. The team works across creative APIs, content scanning, AI-assisted auditing, malware detection, policy enforcement, and operational analytics, while modernizing distributed services on Azure and improving experiences for advertisers, publishers, and internal partners. The role drives technical solutions that advance AI capabilities and engineering practices across the software development lifecycle. It involves defining requirements with stakeholders, leading architecture and testing strategies for complex systems, and building extensible solutions that can scale across teams. The engineer provides technical leadership through mentoring, debugging, code-quality improvements, and adoption of effective engineering patterns; develops deployment automation and operational readiness; and partners with other teams to ensure services meet security, reliability, compliance, and integration requirements before launch. The role also evaluates emerging technologies and shares practices that improve engineering across the organization. Employees who live within a 50-mile commute of a designated Microsoft Hub in the U.S. are expected to work in the office at least four days per week, subject to local law and jurisdictional variation. The position includes serving as a designated responsible individual in an on-call rotation, leading incident mitigation and retrospectives, and improving service reliability and supportability.

Requirements

Bachelor’s degree in Computer Science or a related technical field and 4+ years of technical engineering experience coding in languages such as C, C++, C#, Java, JavaScript, or Python, or equivalent experience.
Experience leading engineering work involving complex systems, architecture, testing strategies, and code delivery.
The role requires participation in an on-call rotation.

Nice To Haves

Master’s degree in Computer Science or a related technical field and 6+ years of technical engineering experience coding in languages such as C, C++, C#, Java, JavaScript, or Python; or a bachelor’s degree in Computer Science or a related technical field and 8+ years of such experience; or equivalent experience.

Responsibilities

Partner with product managers, engineering leads, security and privacy specialists, and customer support teams to define feasible requirements and measurable outcomes for creative processing, audit quality, API performance, and policy enforcement.
Use customer feedback and service data to identify unmet needs, including security, privacy, accessibility, and globalization needs; establish feedback loops and success measures tied to customer value.
Lead architecture and design for complex APIs, distributed workers, event-driven pipelines, and data services across creative ingestion, scanning, scoring, search, and publishing.
Evaluate design alternatives, clarify trade-offs, identify dependencies, and align service contracts, ownership, and delivery plans across teams.
Design for scalability, resiliency, disaster recovery, security, privacy, and sustainable infrastructure cost, including migration of legacy systems to Azure.
Own test strategies covering integration, performance, security invariants, negative cases, and regression prevention; mentor engineers in testable design and improve automated-test reliability, speed, and diagnostic value.
Improve AI-assisted requirements, design, coding, testing, and operations; validate AI-generated assets for accuracy, security, and maintainability, and coach peers in Responsible AI controls.
Experiment with AI tools and agent-assisted workflows and recommend adoption based on demonstrated value.
Apply SDLC and engineering health measures, including Accelerate, SPACE, and the Engineering System Success Playbook, to improve team practices.
Lead by example and mentor engineers across teams in delivering extensible, maintainable, secure, well-tested, and performant code.
Establish reusable patterns and metrics that improve quality, stability, testability, and operating cost.
Lead debugging across application, data, and infrastructure boundaries using tests, logs, telemetry, and verification of assumptions; resolve ambiguous failures and communicate risks and mitigations.
Conduct substantive code and test reviews that improve correctness, diagnosability, security, and maintainability; integrate automated source analysis into development and builds.
Build security and compliance into designs, code, and operations using least-privilege access, threat modeling, security invariants, deployment gates, artifact integrity, and privacy-aware telemetry.
Maintain audit evidence and apply relevant Microsoft standards and regulations, including AI safety requirements.
Establish end-to-end validation, live-site coverage, and escalation paths with partner teams before launch.
Improve developer tooling and reusable engineering practices; evaluate emerging technologies and responsible reuse of internal or open-source components, and share knowledge through mentoring and technical discussions.
Translate multi-team initiatives into milestones, estimates, and release plans.
Partner with product and data science teams on feature flags and experiments with success and guardrail metrics, using results to guide rollout and shipping decisions.
Automate CI/CD and production deployment toward zero-touch operation; validate changes in production-like environments and manage secure dependencies.
Plan progressive rollout, capacity, failover, backup and restore, and explicit rollback criteria.
Design instrumentation, dashboards, and alerts for availability, latency, throughput, audit coverage, and safety mechanisms.
Use telemetry to improve reliability and efficiency while respecting privacy and data-retention requirements.
Serve as a designated responsible individual in the on-call rotation; lead incident mitigation, communicate impact and status, coordinate partner teams, and restore service within agreed service-level expectations using minimum required access.
Lead incident retrospectives and durable repairs that reduce recurrence; improve troubleshooting guides, runbooks, tests, and automation, and mentor engineers in reliable service ownership.