Top Tech Jobs & Startup Jobs in Austin, TX

Leads product strategy, vision, roadmap, discovery, and backlog prioritization for digital products. Translates customer and business needs into features and user stories, partners with technology and business teams, monitors product metrics, and drives customer adoption through experimentation, market insights, and go-to-market initiatives.

Leads architecture, design, development, testing, deployment, monitoring, and production ownership for complex software products. Guides engineering practices including TDD, pair programming, CI/CD, microservices, and distributed systems. Provides technical leadership across product teams, facilitates Agile ceremonies, resolves technical issues, and manages medium to large engineering teams. Advises direct reports on priorities, risks, budgets, administrative policies, and sourcing decisions while driving KPI achievement.

Leads enterprise data architecture strategy, modernization, and implementation across cloud data platforms, data lakes, lakehouses, warehouses, analytics, and AI environments. Designs secure, scalable data models, ingestion and integration patterns, and cloud-native architectures. Builds prototypes, evaluates emerging technologies, guides engineering teams, and drives adoption of strategic data products. Partners with executives, business stakeholders, architects, security, and delivery teams to establish enterprise data practices and architectural direction.

Performs property and casualty insurance reserving projects using actuarial, statistical, and predictive modeling techniques. Reviews data quality, develops moderately complex reserving methodologies, manages project contributions, documents analyses, communicates findings to technical and nontechnical stakeholders, and recommends assumptions and methodologies. The role requires a bachelor’s degree and active pursuit of Casualty Actuarial Society examinations.

Leads data engineering teams in designing, developing, and supporting scalable batch and streaming data solutions. Responsibilities include data pipeline development, architecture, governance, security, platform optimization, production support, technical mentorship, stakeholder collaboration, and delivery leadership. The role requires hands-on engineering with Python or similar languages, modern data technologies, cloud platforms, DevOps practices, and people-management responsibilities.

Lead Client Legal Services analytics strategy and team development. Own Power BI reporting products, Microsoft Fabric data solutions, governance, predictive modeling, responsible AI adoption, ROI measurement, and executive insights. Partner cross-functionally to improve legal operations, litigation outcomes, staffing, capacity, cost management, quality, and workflow optimization while building scalable analytics capabilities and institutional knowledge.

Provides strategic legal counsel on U.S. state privacy laws, GDPR, data governance, AI regulations, advertising technology, FCRA, and data-driven transactions. Advises product, marketing, technology, and data teams on consent, data use, licensing, disclosures, retention, and regulatory risk. Requires complex legal analysis, risk-benefit assessments, transaction support, and cross-functional collaboration to enable innovation while managing legal exposure.

Develop and support enterprise full-stack applications using Java, Spring Boot, Python, React, and cloud technologies. Build secure APIs, microservices, integrations, chatbot interfaces, and conversational UI features. Deploy cloud-native applications with Azure or AWS, Docker, and Kubernetes while contributing to CI/CD, testing, monitoring, security, and architecture. Collaborate with product, engineering, architecture, and business teams in an agile environment.

Develops data infrastructure, analytics solutions, prototypes, and enterprise data assets supporting data science and predictive modeling. Collaborates with data scientists, engineers, and business partners to define requirements, build and test solutions, support user acceptance, and deliver rapid data engineering work tracks. Uses SQL, Python, and Spark for agile data analysis and parallel processing. Also contributes to proof-of-concept designs, documentation, process improvement, and team mentoring.

Develop and enhance full-stack digital products across frontend and backend systems. Responsibilities include designing, coding, testing, troubleshooting, maintaining applications, contributing to CI/CD and cloud-native practices, and collaborating through Agile ceremonies, paired programming, and knowledge sharing. Senior and Lead engineers additionally mentor teams, influence technical strategy, guide system design, and drive cross-product engineering direction.