AI Growth Intelligence Engineer (NewsBreak Venture, New Grad)

Overview We’re looking for a curious, technically strong software engineer to join our Corporate Ventures and AI Operations team. This is a hybrid role sitting at the intersection of backend engineering, ML infrastructure, and revenue systems – you’ll build and maintain the pipelines and services that power our ads platform, engineer the recommendation systems that keep users coming back, build the tools that automate commission and quota-setting for our ad sales team, and work closely with business stakeholders to ship production systems that turn data into decisions. You care about the milliseconds between a user opening the app and finding something they love. You think about what makes someone stay, subscribe, and come back tomorrow – and you write the code that makes that happen at scale. Audience Retention & Performance Systems Help build instrumentation and monitoring systems that track performance signals (load times, stream quality, error rates) to ensure users experience fast, flawless products across web, app, and live streams. Contribute to backend services and dashboards that track engagement and retention metrics – session length, scroll depth, return rate, and drop-off points. Build tooling to help surface friction in the user journey, working with product and engineering to ship fixes. Support the experimentation infrastructure used to test retention‑boosting product changes. Recommendation & Personalization Systems Contribute to recommendation algorithms and services that surface the right content to the right user at the right moment, under the guidance of senior engineers. Help build the data infrastructure (feature pipelines, training datasets, feedback loops) that keeps recommendation models fresh, accurate, and served in production with low latency. Help instrument personalization systems to measure impact on session time, click‑through rates, and long‑term retention. Partner with content and product teams to ship recommendation output into intuitive, performant user experiences. Data & Backend Engineering Build and maintain components of data pipelines and services that process large‑scale ads, user event, and engagement data. Write clean, well‑tested code (SQL, Python, PySpark, or similar) to transform raw data into reliable, analysis‑ready datasets and APIs, with code review support from senior team members. Contribute to the data architecture supporting ad‑tech integrations, paywall flows, and subscription checkout – helping ensure these monetization surfaces are instrumented, reliable, fast, and resilient. Help build automated checks to monitor data quality and flag data integrity issues. Partner with platform and engineering teams to keep systems scalable, observable, and well‑documented. Revenue Operations Tooling Support the engineering behind the commission calculation system for the ad sales team, with a senior engineer owning overall design – focusing on accuracy, reliability, and auditability. Help build tools that support sales quota‑setting, working alongside senior engineers and Finance partners who own the underlying business logic. Contribute to simulation tools that model commission payout scenarios and the cost/incentive impact of quota and comp plan changes. Work with cross‑functional partners (product, marketing, sales) to understand their tooling needs and help ship solutions. Help build alerting to surface trends and anomalies in ads performance. Help automate recurring operational reporting to free up team bandwidth. Benefits Work from home opportunities Paid time off and paid holidays Paid parental leave FSA and commuter benefit programs Team activity budget Top‑tier 401(K) plan with company matching Health, dental, and vision care for you and your family Qualifications Solid software engineering fundamentals — data structures, algorithms, basic system design. Proficiency in at least one general‑purpose programming language (Python, Java, Scala, or Go) and working knowledge of SQL. Bachelor’s or Master’s degree (recent grad or up to ~2 years of experience) in Computer Science, Software Engineering, or a related technical field. Coursework, academic projects, or internship experience involving data pipelines, backend services, or applied software systems. Exposure to distributed data processing concepts (Spark, Hive, or similar) is a plus, not required. Basic understanding of A/B testing and experimental design principles. #J-18808-Ljbffr NewsBreak