Top Tech Jobs & Startup Jobs in Austin, TX

Lead the product strategy for Scribd's internal developer and agentic platforms: unify AI workstreams, own internal app/plugin/agent runtimes, translate functional needs into platform requirements, drive cross-functional adoption and metrics, and run internal rollouts and evaluation to prove impact.

Design, build, and optimize event-driven, distributed backend systems and APIs in Python for large-scale content metadata extraction and enrichment. Deploy and operate resilient AWS-based pipelines, collaborate with ML teams to integrate models, and ensure system performance, observability, and data integrity.

Own and scale quality infrastructure for web engineering during a transition from a monolith to microfrontends. Build shared testing frameworks, CI/CD quality gates, metrics, and AI-enabled tooling to improve test ownership, reliability, and developer productivity. Mentor engineers, define testing strategy across unit/component/integration/contract layers, and create verification loops for agentic code generation.

Build and optimize backend distributed systems to extract, enrich, and process metadata at scale. Integrate LLMs and ML models into production pipelines, ensure data quality and monitoring, collaborate with ML engineers and product, and maintain infrastructure, security, and performance of metadata systems.

Lead and scale paid social advertising across Meta, TikTok, Reddit, and emerging platforms to drive user acquisition for subscription products. Own budgets, audience targeting, structured testing, creative collaboration, AI-accelerated experimentation, analytics, attribution and incrementality work, and conversion rate optimization across landing pages. Communicate results and build reusable playbooks for the performance marketing team.

Lead technical direction and architecture for the Fable backend, own platform reliability (databases, CI/CD, queues, observability), run incident response and postmortems, mentor engineers, collaborate cross-functionally with product/design/ML, and build platform capabilities enabling faster, safer delivery.

Design, build, and scale event-driven, distributed backend systems in Python to extract and enrich metadata at massive scale. Lead architecture, mentor engineers, integrate ML/LLM components, optimize performance, and ensure observability and reliability across AWS-based pipelines.

Build and optimize frontend signup and activation experiences using modern JavaScript and TypeScript. Collaborate with product, design, and analytics to implement high-converting, accessible, and performant user flows, own features from design through implementation, and participate in experimentation and personalization to improve conversion.

Lead AI engineering on the Data Platform: build Databricks Apps deployment paths, construct an AI layer over the Medallion Architecture and semantic layer, enable LLM/NLP systems and agentic workflows, embed AI tooling in the developer lifecycle, enforce guardrails for production safety, define metadata/modeling patterns, and mentor engineers to accelerate AI adoption.

Lead and scale Scribd's Data & Analytics organization across Product Analytics, Data Science, and Analytics Engineering. Build operating model, data governance, experimentation frameworks, AI-native workflows, and infrastructure to accelerate insight delivery. Develop director-level leaders, recruit talent, and embed data-driven decision-making at the executive level to drive growth, retention, and portfolio-wide strategy.