Principal Software Architect (Platform)

OPERATIVE OVERVIEWOperative builds the software that powers the business of advertising for the world's leading media companies. Our platforms manage the full advertising lifecycle — from sales planning and order management to trafficking, analytics, and billing — across linear TV, streaming, and digital channels.Built on a modern, cloud-native SaaS architecture with microservices at its core, the Operative platform is engineered to handle the scale and operational demands of the world's largest broadcasters and publishers. Operative is actively developing AI Agents — both to enhance the capabilities of our platform and to augment how our engineering teams work. Engineers at Operative have access to AI tooling as a standard part of their workflow, and we are investing in building increasingly autonomous agents that accelerate development.Position OverviewOperative is seeking an experienced architect with a strong hands-on engineering background and a demonstrated ability to operate independently and drive the technical quality of the teams and codebases they engage with. This individual will serve as a senior technical authority across Operative's platform engineering disciplines, spanning backend services, distributed data infrastructure, and cloud-native architecture.This role represents a significant opportunity to shape how a complex, high-scale platform evolves — identifying the highest-priority technical investments, establishing the standards and patterns the broader team will follow, and driving those initiatives from inception through delivery. AI adoption and maturity is a strategic priority at Operative, and this individual will play a direct role in advancing both the use of AI within engineering workflows and the development of agentic capabilities within the platform itself. The successful candidate will bring both architectural breadth and hands-on depth, and will be motivated by the opportunity to work at the intersection of modern platform engineering and applied AI.Key ResponsibilitiesArchitect and lead delivery of complex, cross-functional initiatives spanning backend services, data pipelines, and cloud infrastructureDrive the adoption and maturity of AI within engineering workflows, including agentic tooling, AI-assisted development practices, and the integration of autonomous AI agents into platform capabilitiesIdentify systemic technical challenges across reliability, performance, scalability, and observability, and own the path to resolutionDefine and uphold engineering standards across code quality, testing practices, API design, data modeling, and deployment patternsMake well-reasoned architectural decisions in ambiguous or rapidly evolving situations, and communicate those decisions clearly to technical and non-technical stakeholdersEngage across the full technology stack; this role requires both breadth and depth, with the ability to move fluidly between system-level architecture and hands-on implementationPartner with Product and business stakeholders to translate complex requirements into coherent technical strategyProvide mentorship and technical guidance to engineers across the broader global team through design reviews, documentation, code review, and direct collaborationServe as a senior escalation point for complex or high-impact engineering problemsQualities and Working StyleBeyond technical depth, Operative is looking for specific qualities that define how this individual will work:Operates with a high degree of autonomy and self-direction; identifies what needs to be done without requiring close oversightHolds strong technical opinions grounded in experience, while remaining pragmatic about tradeoffs and contextApproaches ambiguity as a problem to be solved rather than a barrier to progressRemains hands-on as a practitioner; this is an engineering leadership role, not a purely advisory oneHas a track record of being a go-to resource for difficult, cross-cutting engineering challengesCommunicates technical concepts effectively to cross-functional audiences, including product and business stakeholdersTechnical RequirementsCandidates should demonstrate strong proficiency across the following areas:Java / Spring BootPythonKafka / Kafka ConnectKubernetesAWSElasticsearchMongoDBSQLRedisServerless / LambdaS3 / Object StorageCI/CD & DevOpsDepth across all areas is not required; candidates should be able to engage effectively across the stack and demonstrate strong expertise in several. Familiarity with the following areas is also valued:Distributed systems design, including event sourcing, CQRS, and saga patternsPlatform observability, including distributed tracing, metrics infrastructure, and structured logging at scaleData pipeline architecture, including stream processing, schema evolution, and backpressure managementSecurity and compliance practices within cloud-native environmentsQualifications10 or more years of software engineering experience with demonstrated scope at the