Hyperscale

Founding Forward Deployed Engineer

San Francisco, CA
Python SQL API
Description

Founding Forward Deployed Engineer

Department: Engineering

Location: San Francisco

Employment Type: FullTime

Founding Forward Deployed 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 Forward Deployed Engineer who will be responsible for deploying, configuring, and optimizing Hyperscale's agentic AI platform at customer sites. You'll work directly with enterprise carriers to integrate our product into their operations, then iterate rapidly based on real-world performance and feedback.

You'll be working on the frontier of applied AI deployment: taking sophisticated agentic systems from demo to production in complex operational environments. This means understanding customer workflows deeply, configuring AI agents to handle their specific use cases, and solving technical integration challenges in real-time - all while the technology itself is rapidly evolving.

This is a highly technical, customer-facing role where you'll split time between customer sites and working with our product team. If you like being in the field, solving hard problems on the fly, and seeing immediate impact from your work, this role is for you.

What You'll Do

Customer deployment and integration

  • Own end-to-end deployment of Hyperscale's platform at enterprise customer sites, from scoping to go-live

  • Work directly with carrier operations teams to understand their workflows, pain points, and requirements

  • Configure and customize our agentic AI system to handle customer-specific use cases, call flows, and business logic

  • Integrate our platform with customer systems (TMS, dispatch software, driver apps, etc.) via APIs and custom connectors

  • Troubleshoot technical issues in real-time and ensure successful production launches

Agent optimization and tuning

  • Monitor AI agent performance in production and identify opportunities for improvement

  • Iterate on agent behavior, prompts, workflows, and guardrails based on real customer interactions

  • Work with product and engineering teams to translate field learnings into platform improvements

  • Build customer-specific tooling, scripts, and configurations to maximize automation rates and quality

Technical consultation and enablement

  • Serve as the technical point of contact for enterprise customers during deployment and early adoption

  • Train customer teams on how to monitor, configure, and optimize the platform

  • Create deployment runbooks, integration guides, and best practices documentation

  • Proactively identify expansion opportunities and new use cases within existing accounts

Product feedback and collaboration

  • Bring frontline insights back to product and engineering teams to inform roadmap and priorities

  • Participate in customer calls, demos, and technical scoping conversations alongside sales

  • Help shape how we build agentic features that work reliably in diverse operational environments

  • Contribute to internal tooling that makes deployments faster and more scalable

Who You Are

  • 3-5+ years of software engineering or solutions engineering experience, with a strong technical foundation

  • Comfortable with full-stack development, APIs, databases, and system integrations

  • Track record of working directly with customers in technical or deployment roles

  • Strong problem-solving skills and ability to debug issues across unfamiliar systems

  • Excellent communication skills - you can translate between technical and operational stakeholders

  • Highly adaptable and comfortable with ambiguity, rapid iteration, and changing priorities

  • Willing to travel regularly to customer sites (expect 30-50% travel)

Nice to Have

  • Experience deploying AI/ML products or other complex technical systems in production

  • Background in logistics, trucking, fleet operations, or adjacent industries

  • Prior work as a solutions engineer, implementation engineer, or forward deployed engineer

  • Experience with enterprise integrations, ETL pipelines, or middleware platforms

  • Startup experience or comfort operating in fast-moving, high-autonomy environments

  • Scripting and automation skills (Python, SQL, etc.)

Location

San Francisco preferred (in-person when not traveling). We move quickly and value tight feedback loops across deployment, product, engineering, and customers.

Why Hyperscale

  • Real product in production with major US fleets

  • Clear ROI and strong metrics already working in the wild

  • Work hands-on with cutting-edge agentic AI technology in high-stakes production environments

  • Direct customer exposure and immediate feedback loops - see your work drive real operational outcomes

  • Build the deployment playbook and forward deployed function from day one, with a path to leadership as we scale

  • Backed by top VCs and growing quickly - doubling the team in the first half of the year

To apply: Send a note with your LinkedIn/GitHub and 1-2 examples of work you're proud of (a deployment you led, an integration you built, a customer problem you solved, or anything that shows how you think and execute).

Hyperscale
Hyperscale

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