Top Tech Jobs & Startup Jobs in Austin, TX

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

As a software engineer, you'll build and iterate on the product across the stack, engaging with customers and collaborating with the team to shape the company culture and technology.

Senior individual contributor responsible for generating and converting enterprise new-client revenue across North America. Own $10M+ net new targets, personally originate and close complex $5M–$15M engagements, lead C-suite conversations, negotiate high-value agreements, navigate procurement and legal processes, and partner with sales and finance to protect margin and scale enterprise pipeline.

Deploy agentic AI solutions in strategic enterprise accounts: discover requirements, design multi-turn agent workflows, integrate AIR Pro with customer systems, ensure compliance and observability, drive measurable ROI and support go-to-market and product feedback.

Lead architecture and implementation of scalable data systems and pipelines from ingestion to delivery. Own ambiguous, high-impact integrations, improve data quality and reliability, adopt AI-augmented engineering, mentor engineers, and collaborate with Product, ML, and customer teams to ship production solutions.

Lead the design and build of automation infrastructure for GTM, enhancing sales and marketing efforts through advanced engineering solutions.

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

Design, build, and maintain scalable backend services in Elixir/Phoenix. Develop high-availability APIs, distributed systems, data pipelines, and background job processing. Collaborate with AI and product teams, improve observability and reliability, influence architecture, establish testing and delivery best practices, and mentor engineers.

Build and extend Kubernetes orchestration for AI inference: implement CRDs/controllers in Go, design high-performance ingress/load-balancing, implement GPU-aware autoscaling (HPA/VPA), tune scheduler/resource management, and ensure HA for platform components.

Lead architecture and implementation of complex HubSpot instances, design RevOps-aligned data schemas and native integrations, build lead scoring, attribution, reporting, and governance to optimize revenue operations.