Principal Software Engineering Manager, AI Experiences

Quick Facts

• Role: Principal Software Engineering Manager, AI Experiences

• Team scope: Infrastructure, Operations, and Shared Tech for a real-time advertising platform

• Key focus: Low-latency distributed systems, platform reliability, operational excellence, and engineering productivity across hybrid on-premises and Azure

Description

You will lead a team that provides shared infrastructure and services for real-time advertising, including distributed caching, low-latency decision-service integration, traffic management, and high-volume logging and streaming pipelines. You will combine people leadership with deep technical judgment to advance platform architecture, operational excellence, and developer productivity, and to integrate model-backed capabilities into latency-sensitive production serving.

Responsibilities

• Lead and develop engineers: hire, coach, grow, and foster inclusive technical excellence and accountability

• Own roadmap and delivery: translate platform/product needs into architectural plans and measurable outcomes while balancing reliability, security, technical debt, and cost

• Guide shared-platform architecture: evolve reusable services, libraries, interfaces, and runtime components with clear ownership boundaries and compatibility

• Advance low-latency engineering: improve concurrency, asynchronous execution, memory safety, and resource efficiency with strong design review and automated testing

• Modernize distributed caching/state services: lead client/server integration, migrations, capacity planning, replication/failover, and observability

• Enable model-backed serving and traffic management: integrate model scores/decisions with latency budgets, correctness, fallbacks, and experimentation controls

• Evolve logging and streaming infrastructure: improve buffering, batching, transport, throughput, backpressure handling, data integrity, and recovery

• Lead safe infrastructure modernization: deliver infrastructure-as-code and staged Azure migrations with cutovers and rollback plans

• Drive operational excellence: improve SLOs, monitoring/alerting/diagnostics, on-call, incident response, and blameless postmortems

• Improve developer productivity and secure delivery: advance CI/CD, deployment automation, configuration management, and reusable tooling with security/privacy embedded

Requirements

• Bachelor’s degree in Computer Science or related technical field AND 6+ years technical engineering experience coding in C/C++/C#/Java/JavaScript/Python (or equivalent experience)

• 3+ years of people management experience (coaching, performance management, career development)

• Experience designing, delivering, and operating large-scale distributed systems (performance-sensitive backend services)

• Experience leading cross-team initiatives for shared platforms/infrastructure/modernization

• Strong software architecture and production reliability knowledge (concurrency, resource management, distributed failure modes)

• High-performance C/C++ engineering on Linux (multithreading, async I/O, memory ownership, profiling, efficient data structures)

• Experience building shared libraries/foundational services with interface evolution and backward compatibility

• Experience with distributed caches/key-value systems (Aerospike/Garnet/Redis or similar) including replication/failover/capacity planning/client integration

• Experience with Kafka or comparable streaming and high-throughput logging/data pipelines

• Experience integrating ML scores/model-backed decisions into latency-sensitive production services

• Experience with traffic shaping, rate limiting, admission control, or similar mechanisms

• Experience operating Azure and hybrid infrastructure (VM scale sets, networking, storage, IaC such as Terraform/Bicep)

• Experience with configuration management tools (Puppet or comparable), CI/CD pipelines, and automated build/test environments

• Experience delivering migrations using feature flags, experimentation/shadow traffic, staged rollouts, and rollback strategies

• Experience with observability (Grafana/OpenTelemetry) and operational practices (SLOs, incident management, operational automation)

Benefits

• Competitive base pay range (U.S.): USD 142,800–274,800 per year; Bay Area and NYC metro: USD 188,000–304,200 per year

• Eligible for benefits and other compensation (per company pay/benefits information)

• Hybrid work expectation for eligible U.S./non-U.S. commute rules starting Jan 26, 2026 (4 days per week from office or per local law)