Top Tech Jobs & Startup Jobs in Austin, TX

Lead developer relations as the company’s first DevRel hire. Create technical content, demos, examples, and projects; speak at conferences, meetups, and podcasts; build relationships with engineering teams and technical communities; gather product feedback; establish the company as a leading voice in AI-driven engineering; and grow its social following.

Lead client engagements on benefits strategy, plan design, open enrollment, and administration. Stabilize operations, manage carriers/brokers, execute transitions and platform migrations, ensure compliance, advise on cost optimization and multi-state/global expansion, and expand client relationships.

Own the organization’s end-to-end YouTube strategy, including channel architecture, content cadence, audience growth, editorial direction, packaging, analytics, experimentation, and monetization. The role partners with production, creative, marketing, social, and partnerships teams; develops growth playbooks and performance reporting; identifies revenue opportunities; tracks platform and creator trends; and coaches teams on YouTube best practices.

Designs, manages, and optimizes CI/CD pipelines; builds and maintains scalable, secure AWS infrastructure; and partners with development teams to support efficient agile deployments. The role requires extensive DevOps experience, AWS expertise, Docker and Kubernetes proficiency, advanced English and Spanish communication skills, and a focus on resilient, high-performance engineering.

Leads and mentors an engineering team building scalable web applications for fintech and media products. Responsibilities include setting technical architecture, guiding engineering decisions, partnering with product and design stakeholders, maintaining modern web applications, improving reliability and performance, supporting delivery planning, and adopting AI-assisted development and automation. The role combines hands-on software engineering, people management, technical strategy, and cross-functional collaboration.

Partners with sales, engineering, vendors, and customers to define warehouse robotics solutions. Leads technical discovery, site visits, system design, ROI modeling, proposals, test plans, and executive presentations. Supports solution scoping, WCS/WMS integrations, statements of work, MSA negotiations, implementation planning, and post-sale technical advising while feeding customer insights to Product.

Cultivate and steward a portfolio of 350–600 mid-level donors, securing $6,000–$10,000 gifts and developing prospects for major giving. Build personalized donor relationships, manage qualification and cultivation pipelines, use segmentation and engagement metrics, maintain CRM records, and communicate organizational impact. The role requires regular U.S. travel, cross-functional collaboration, and expertise in charity: water’s programs and WASH issues.

Lead the architecture, development, optimization, and operation of production LLM and AI automation systems. Design capabilities including agents, retrieval, code generation, tool use, model routing, evaluation, and observability. Drive platform modernization, scalability, reliability, architecture, and code quality while mentoring engineers and influencing technical practices across teams. Build prototypes, establish engineering standards, conduct reviews, and communicate complex technical concepts through documentation and cross-functional collaboration.

Own client-facing technical workstreams from discovery and requirements through solution design, build, testing, deployment readiness, handoff, and hypercare. Lead client sessions, make design decisions, manage scope and dependencies, review team output, and ensure production readiness. Apply generative AI throughout delivery and within client solutions, particularly for consumer-brand use cases including customer care, commerce, fulfillment, POS, and customer data. Coach associate engineers and contribute to estimates, statements of work, reusable accelerators, and growth opportunities.

Own the evaluation, selection, optimization, and production deployment of large language models powering legal and medical document workflows. Build EvalOps and monitoring frameworks, benchmark model quality, cost, speed, and resilience, manage model transitions, optimize RAG and orchestration pipelines, and reduce hallucinations. Partner with product and go-to-market stakeholders while independently implementing changes across staging and production.