Founding Senior Software Engineer

HyperscaleSan Francisco, CA
Onsite

About The Position

Founding Senior Software Engineer (SF In-Person Preferred) About Hyperscale Hyperscale is building the AI-native intelligence layer for physical operations - starting with trucking carriers. We're a team of ex-Samsara engineers and fleet operators automating the highest-volume office workflows (driver support, load coordination, scheduling) with agentic AI that actually moves the needle. Our products are deployed with some of the largest fleets in the US, autonomously handling ~70% of inbound calls with strong customer satisfaction. We're a small team, moving fast, backed by top investors and advisors. The Role We're hiring a Founding Senior Software Engineer who will help build the core product infrastructure that powers Hyperscale's agentic AI platform. You'll work directly with the founders and across the stack - from backend systems to real-time voice interfaces to customer-facing features. You'll be working on cutting-edge applied AI challenges: building production agentic systems that autonomously handle complex, multi-step workflows in real-world operations. This means solving hard problems in agent orchestration, real-time decision-making, tool use, and human-AI interaction patterns - not just integrating LLM APIs, but architecting the intelligence layer that makes autonomous operations reliable at scale. This is a broad, hands-on role where you'll own significant parts of the product and have the opportunity to shape our engineering culture from day one. If you like building from zero, shipping fast, and solving hard problems close to real customer impact, this role is for you.

Requirements

  • 5+ years of software engineering experience, with demonstrated ability to build and ship full-stack applications
  • Strong fundamentals in backend systems, databases, APIs, and web applications
  • Comfortable working across the stack and learning new technologies quickly
  • Track record of owning complex features or systems from design through deployment
  • Experience building production systems at scale with attention to reliability and performance
  • Strong judgment about technical tradeoffs and when to optimize for speed vs. robustness
  • Excellent communicator who can explain technical concepts to non-technical stakeholders

Nice To Haves

  • Experience with real-time communication systems, voice applications, or telephony
  • Background in AI/ML product development, agentic systems, or integrating LLMs into production systems
  • Prior work in logistics, operations, or enterprise SaaS
  • Experience at an early-stage startup or as a founding engineer
  • Open source contributions or side projects that demonstrate your craft

Responsibilities

  • Engineering across the stack: Build and own core product features end-to-end, from data models to user interfaces (including conversational/agentic UX)
  • Design scalable backend systems that power our AI agents in production environments, including agent orchestration, memory systems, and tool execution pipelines
  • Work on real-time communication infrastructure handling thousands of customer interactions
  • Ship features that directly impact customer outcomes and business metrics
  • Infrastructure and reliability: Build robust, observable systems that handle enterprise-scale workloads with autonomous agents in the loop
  • Own deployment pipelines, monitoring, and incident response
  • Make pragmatic technical decisions that balance velocity with quality and maintainability
  • Establish engineering practices and patterns that will scale with the team
  • Cross-functional collaboration: Work closely with founders, customers, and go-to-market teams to understand requirements and iterate quickly
  • Translate customer problems into elegant technical solutions, including designing agentic workflows and interaction patterns
  • Participate in technical discussions and architecture decisions
  • Help evaluate and integrate new technologies and tools across the rapidly evolving AI landscape
  • Team and culture building: Set the bar for code quality, system design, and engineering excellence
  • Mentor and collaborate with engineers as the team grows
  • Shape our engineering culture, processes, and technical standards
  • Contribute to hiring and building out the engineering team

Benefits

  • Work on the frontier of practical AI engineering - agentic systems, real-time voice, and enterprise infrastructure
  • Define the technical foundation for a category-defining product
  • Build the engineering team and culture from day one, with a path to technical leadership as we scale
  • Backed by top VCs and growing quickly - doubling the team in the first half of the year
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