Top Tech Jobs & Startup Jobs in Austin, TX

Build and optimize scalable frontend applications for Seekr’s AI platform using React and Next.js. Collaborate with ML, backend, DevOps, QA, and Product Design teams to rapidly deliver performant web features. Contribute to technical direction, automated testing, API integration, deployments, and continuous improvement of frontend architecture and user experiences.

Lead product strategy and roadmap for AI Ready Data capabilities—data ingestion, transformation, enrichment, synthetic data, and tooling for retrieval, fine-tuning, evaluation, and agent workflows. Write product specs, partner with engineering, research, design, and GTM, translate experiments into scalable features, work with customers to surface requirements, and define success metrics to monitor adoption and performance.

Embed with client teams to productionize AI: design data pipelines and retrieval frameworks, fine-tune and deploy LLMs and agentic workflows, containerize and orchestrate across cloud and on-prem, optimize inference and monitoring, and codify deployment best practices to scale trustworthy, explainable AI solutions.

Lead and hands-on manage Seekr's AI infrastructure: design, build, and scale Kubernetes-based systems across cloud, on-prem, and edge; mentor engineers; automate operations; handle incidents and security; collaborate with software teams to ensure reliability, performance, and observability.

Design and build explainable and contestable AI capabilities for models and agents. Develop hallucination detection, continual-learning systems, and production AI features from research prototypes. Contribute across model development, inference, deployment, monitoring, evaluation, and performance optimization. Partner with product, design, and customer teams to deliver trustworthy AI workflows. The role requires strong Python and software engineering skills, modern AI systems experience, and the ability to bridge research and production engineering.

Design and productionize explainable and contestable AI capabilities for LLM, VLM, agent, and RAG systems. Develop hallucination mitigation, continual-learning, evaluation, inference, deployment, monitoring, and retrieval solutions. Translate research into production features, optimize model serving, and collaborate with product, design, and customer teams. The role requires strong Python and software engineering skills, research-to-engineering fluency, and experience evaluating complex AI tradeoffs.

Lead the reliability, stability, observability, and scalability of Seekr’s software platform. Design and implement systems, networks, and services that meet SLAs; develop monitoring, automation, and failure-detection solutions; conduct load testing; manage observability tools; troubleshoot production and deployment issues; and support incident response. Collaborate closely with software engineering teams across hybrid cloud and on-premises environments.

Build and scale applications and tools powering AI products, agents, and enterprise solutions. Responsibilities include shipping production-ready features, shaping scalable and reliable architecture, mentoring engineers, driving technical decisions and engineering best practices, collaborating with Product, QA, and business teams, and translating abstract ideas into actionable engineering work. The role requires expertise in Python, distributed systems, APIs, databases, containers, streaming technologies, testing, CI/CD, and AI-assisted development.

Build SeekrFlow Edge Builder, a platform for packaging, deploying, and operating trustworthy AI solutions across edge, cloud, on-premises, disconnected, and air-gapped environments. Responsibilities include developing orchestration, lifecycle management, model serving, optimization, security, observability, testing, APIs, diagnostics, and recovery capabilities. The role requires collaboration across AI, platform, infrastructure, security, product, and customer engineering teams, plus technical documentation and troubleshooting across complex deployment environments.

Own end-to-end product design for major areas of an enterprise AI platform. Lead user discovery, systems-level UX, information architecture, interaction frameworks, prototyping, design system evolution, and implementation specifications. Partner closely with Product and Engineering to navigate technical constraints and roadmap tradeoffs. Design for technical and enterprise users, including AI/ML engineers, data scientists, domain experts, and executives.