Top Tech Jobs & Startup Jobs in Austin, TX

Own a defined enterprise territory to drive revenue by selling SaaS solutions into CFO/CIO organizations. Build pipeline, lead complex consultative deals, negotiate contracts, forecast in Salesforce, and coordinate internal resources to deliver proposals and demos.

As a Data Engineer, you will build and maintain data pipelines, convert data into metrics, and operate the platform on AWS. Responsibilities include writing production code, processing data from APIs, and enhancing the orchestration layer using Dagster, while ensuring compliance in a HIPAA-regulated environment.

Support pilots and nonstandard referral workflows by executing manual processes, reconciling data, documenting evolving procedures, identifying risks, and partnering cross-functionally to inform automation and SOP development.

The AI Data Specialist role involves data collection, evaluation, annotation, pairwise comparisons, and tagging across various content types.

The Marketing Data Scientist will analyze data, onboard clients, develop data pipelines in R, and propose improvements to enhance efficiency.

As a Senior Backend Engineer at Akkio, you'll design and build backend systems for an AI-driven platform, lead projects, mentor junior engineers, and optimize cloud infrastructure.

As a Tech Specialist, you will bridge business ideas with digital tools, use AI for automation, troubleshoot issues, and assist the CTO while learning the tech department's operations.

The Solutions Engineer collaborates with sales to meet customer needs, conducts demos, develops proposals, and ensures product implementation and support.

Lead end-to-end credit strategy and underwriting architecture, build scalable decisioning and risk models, monitor portfolio performance, launch credit products, and hire and manage the credit risk and underwriting team while ensuring regulatory alignment.

Own product strategy and roadmap for an agentic AI platform that enables practitioners and AI agents to run defensible tax analysis on trusted data. Define compliance-grade requirements, agent access surface, and data-product contracts. Manage external data sourcing, measure success by practitioner outcomes, and collaborate closely with AI and data engineering leaders to deliver production results.