Top Tech Jobs & Startup Jobs in Austin, TX

Close and grow corporate travel accounts, owning discovery, proposals, negotiation, and pipeline management. Shape pricing, packaging, messaging, and collateral while creating a repeatable sales playbook for a new revenue line. Partner with business development and operations to qualify leads, hand off trips effectively, and secure referenceable customers. The role requires autonomy, consultative selling, comfort with ambiguity, and experience closing B2B deals of at least $50,000.

Own the company’s demand generation strategy and marketing contribution to pipeline. Responsibilities include selecting target markets and channels, managing campaigns and account-based programs, partnering with AWS and technology partners, creating thought leadership and case studies, running events, managing marketing tools, and reporting on performance. The role requires hands-on B2B marketing leadership focused on measurable pipeline and revenue impact.

Open application inviting AI engineers, full-stack developers, data scientists, finance experts and others to apply. Candidates should submit a resume/LinkedIn, links to work (GitHub, Kaggle, portfolio) and a brief note explaining motivation, value they bring, and desired roles or projects.

Owns healthcare and telehealth operations across clinical, provider, pharmacy, fulfillment, customer support, and technology partners. Responsibilities include managing workflows and SLAs, resolving complex patient and partner issues, developing SOPs and playbooks, preparing launches, monitoring operational metrics, and building scalable processes in an ambiguous, regulated environment.

Manage the delivery of multi-site EV charging projects and programs across the United States. Coordinate sales, engineering, construction, procurement, finance, legal, software, and portfolio teams while overseeing contracts, schedules, budgets, risks, quality, scope changes, documentation, reporting, and stakeholder communications. The role also resolves project issues, manages dependencies and critical paths, monitors contractor performance, implements project controls, and ensures compliance with procedures.

Lead SaaS implementations for government customers from discovery through go-live. Configure workflows, permissions, templates, voting processes, portals, and meeting settings; coordinate data migration, testing, launch readiness, and post-implementation support. Train technical and non-technical users, create documentation, troubleshoot application and video issues, and collaborate with Product, Development, QA, Support, and Customer Success. Occasional after-hours support and travel below 30% may be required.

Senior Solutions Engineer responsible for developing and validating healthcare pricing, billing, and bundling logic; partnering with product, data, and engineering; leading technical discovery and demonstrations; guiding customer API integrations and launches; and translating customer feedback into product improvements. Requires strong healthcare revenue cycle, claims, reimbursement, SQL, API, analytical, and customer-facing technical expertise.

Manage a portfolio of construction ERP customers as their primary advisor. Drive adoption, business outcomes, retention, and expansion through success plans, business reviews, stakeholder engagement, health-data analysis, and proactive risk mitigation. Coordinate escalations and solutions with Renewals, Support, Product, Sales, and Professional Services. Translate customer feedback into product improvements while using AI-enabled tools to prioritize opportunities and risks.

Own Slide’s digital marketing engine across lifecycle email, social, website, paid campaigns, events, webinars, and CRM. Build multi-channel campaigns, landing pages, and conversion paths; manage CMS updates, SEO, database hygiene, workflows, reporting, and LinkedIn publishing. Use funnel metrics to improve lead generation and booked demos while partnering with Events, Product, RevOps, Sales, developers, and agencies.

Design, build, deploy, and optimize scalable AI and machine learning systems using large datasets. Develop predictive models, recommendation systems, personalization engines, forecasting solutions, generative AI applications, and production ML pipelines. Collaborate with data, backend, and product teams to integrate models into applications, while monitoring performance, data quality, drift, reliability, and cost. Establish best practices for evaluation, experimentation, reproducibility, and deployment, and research emerging AI technologies.