Top Tech Jobs & Startup Jobs in Austin, TX

Own production reliability for customer-facing radar and weather data services across Azure, colocation, and edge Kubernetes. Refactor C#/.NET services for multi-replica safety, design multi-cluster HA, operate self-managed Kubernetes, improve observability and automation, lead incident response and postmortems, and drive operational excellence and capacity planning.

Lead technical pre-sales discovery and demos, own enterprise implementations and integrations (ATS/HRIS/payroll), build Workato/API/webhook integrations and POCs, manage strategic customer relationships, translate requirements into product priorities, and document scalable runbooks and integration guides.

Build and ship full-stack features for an AI-powered onboarding platform: design UIs, embeddable components, workflow automations, a compliance rules engine, internationalization, and third-party API integrations while ensuring testability and observability.

Lead design and build of end-to-end growth operating systems connecting marketing, sales, partners, product and engineering. Own CRM, analytics, forecasting, AI-assisted workflows, dashboards, and processes from lead to activation to expansion to drive repeatable revenue and product adoption.

Provide central sales operations support: manage CRM and sales data, coordinate meetings/QBRs/National Sales events, support bids/RFPs, track projects and deliverables, improve SOPs, produce reports, and bridge communication between sales, marketing, and leadership.

The Chief of Staff will facilitate strategy execution, improve operational frameworks, and enhance cross-functional alignment within the Data organization at Coursera.

Lead and deliver end-to-end quality engineering solutions: define test strategy, design and implement scalable automation, integrate testing into CI/CD, run functional/non-functional testing (performance, security, data, AI/ML), manage workstream QE planning and execution, communicate risks and readiness to stakeholders, and mentor/coach engineers while contributing to QE practice improvements.

Lead and deliver Sage Intacct implementations from selection through go-live and post-implementation support. Manage multiple projects, oversee build/test/deploy activities, provide end-user training and documentation, advise on improvements, and identify additional services.

Design and govern cloud-native solutions across compute, networking, storage, identity, data, and observability. Lead architecture reviews, define landing zones and reference architectures, drive migrations and cost optimization, embed security/compliance, produce architecture artifacts, mentor teams, and evaluate cloud provider roadmaps.

Own installation, configuration, upgrades, performance tuning, HA/DR, integrations, and day-to-day operations of Windchill or Teamcenter PLM environments. Automate tasks with scripting, monitor platform health, support post-go-live incidents, maintain documentation and runbooks, and mentor junior engineers.

Design, execute, and productionize LLM fine-tuning workflows (supervised, DPO, RLHF). Lead dataset curation, build scalable distributed training pipelines, tune hyperparameters, implement parameter-efficient methods (LoRA/QLoRA), run large GPU training reliably, design evaluations and safety checks, manage model artifacts, and mentor engineers while translating research into production-ready solutions.

Support VBA COE contract by developing and executing manual and automated test strategies for SaaS/PaaS solutions. Create test plans, test cases, test data, and document results. Execute unit, functional, automation, regression, performance, scalability, and UAT testing. Use test management tools (Xray); Provar preferred. Ensure quality delivery and maintain required Public Trust eligibility. US Citizen required.

Serve as a practitioner-facing solutions consultant supporting sales: join discovery and executive meetings, advise on RFPs and product roadmap, represent Euna at conferences, produce thought leadership, and run customer advisory sessions to advance deals and product-market fit.

Design, build, and operate an ML lifecycle platform to enable reproducible training, deployment, and monitoring of models. Implement CI/CD, containerized deployments on Kubernetes, infra-as-code, model observability, and governance. Mentor teams, define shared patterns, and partner with security and compliance to keep ML systems secure and production-ready.