Timescapes - Senior SRE - Austin, TX

Midwestern Interactive Growth Team • Austin, TX

6d • Hybrid

About The Position

Timescapes is seeking a Senior Site Reliability Engineer to build and operate the reliable, scalable systems underpinning its product and engineering teams. This is a broad, hands-on role covering site reliability engineering, ML platform architecture, and applied AI for engineering operations. The engineer will partner with Software, AI, Product, and Hardware teams to make trade-offs involving reliability, security, developer experience, scalability, and cost.

Timescapes is a visual progress tracking solution for complex construction projects. Founded in New Zealand in 2017, the company serves large construction firms across Australia, Canada, New Zealand, and the United States. Its mission is to simplify construction through shared visibility.

The role is hybrid in Austin, Texas, with 2 to 3 days per week in person and flexibility. Timescapes values first-principles problem solving, thoughtful product development, awareness, care, and quality.

Requirements

• Experience building and operating customer-facing production systems and helping design or run production ML infrastructure.
• Ability to diagnose complex failures and support production software.
• Strong engineering fundamentals, including writing maintainable software, automating infrastructure, and reasoning across distributed systems, networking, cloud services, and data-intensive workloads.
• Focus on delivering genuine value from engineering investments and using methodologies and best practices in service of customer outcomes.
• Care about details, question decisions that do not make sense, and clearly explain the rationale behind decisions.
• Comfort discarding initial approaches, learning from production, and treating the first release as the beginning of iteration.
• Adaptability and creativity when working with ambiguity and changing needs.
• Clear, succinct communication and ability to build strong working relationships across written, video-call, and in-person settings.

Nice To Haves

• Experience supporting media-heavy data pipelines, GPU workloads, or computer vision and multimodal models across edge and cloud environments.
• Experience using LLMs or other AI systems to improve developer workflows, observability, incident response, or engineering operations.
• Startup or scale-up experience, including managing competing priorities, rebuilding unscalable processes, and adding appropriate structure without unnecessary bureaucracy.

Responsibilities

• Own the availability, performance, and resilience of production systems, balancing capacity, risk, cost, and operational readiness.
• Define meaningful SLIs and SLOs, strengthen instrumentation and alerting, and improve understanding of system behavior before customers are affected.
• Participate in and improve on-call practices, lead incident response, and turn post-incident learning into lasting improvements.
• Improve cloud infrastructure, deployment pipelines, and environment management to enable safer delivery and reduce operational toil.
• Drive architecture for ML data preparation, model training, evaluation, deployment, monitoring, and iteration in partnership with AI/ML engineers.
• Identify and implement AI-enabled tools and workflows to accelerate diagnosis, improve operational decisions, and reduce repetitive engineering work.
• Partner with Software, AI, Product, and Hardware teams to make sound trade-offs across reliability, security, developer experience, scalability, and cost.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed