Founding Forward Deployed Engineer

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 are a team of ex-Samsara engineers and fleet operators automating the highest-volume back-office workflows (load coordination, scheduling, driver support, and more) with agentic AI. Our product is deployed with some of the largest fleets in the US, autonomously handling ~70% of tasks with strong customer satisfaction. We are small, moving fast, and backed by top investors. The Role We are looking for a Founding Forward Deployed Engineer to own the technical side of our enterprise sales process. You will work directly with the founders, Head of BD, and engineering team: running technical discovery, designing POCs, traveling on‑site to customer locations, and supporting implementation through go‑live. This role blends pre‑sales and post‑sales, and the ideal person can flex across product, engineering, and sales depending on what the moment requires. If you like solving complex integration challenges, translating technical capabilities into business value, and shaping product direction from the field, this role is for you. 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 Technical Discovery and Solution Design Lead technical discovery calls with carrier IT, operations, and executive teams Understand customer workflows, systems (TMS, ELD, dispatch software), and integration requirements Design proof‑of‑concept configurations that map our AI agents to specific customer use cases Document edge cases and requirements to inform the product roadmap Demos, Pilots, and Proof of Value Run tailored product demos tied to each prospect's workflows and pain points Scope and execute pilot programs with clear success metrics (call resolution rate, time savings, CSAT) Build ROI models showing cost savings and efficiency gains Troubleshoot issues during pilots and coordinate with engineering to resolve them quickly On‑Site Customer Engagement Travel to customer sites roughly once a month for one to two days at a time (up to 25% travel in steady state) Embed with customer operations teams to conduct workflow discovery and scope integrations Write code or prototype solutions on‑site when needed to unblock deals or accelerate implementation Technical Sales Support Answer RFPs, security questionnaires, and compliance documentation (SOC 2, data handling, etc.) Lead technical deep‑dives with buyer IT and security teams on architecture, data flows, and integrations Build proposals, integration plans, and implementation timelines Address technical objections early and build internal champions Onboarding and Post‑Sales Scope integrations (APIs, webhooks, data pipelines) with engineering for new customers Support initial deployment: data mapping, workflow configuration, testing, and go‑live Train customer teams on configuration, agent tuning, and performance monitoring What Success Looks Like (First 90 Days) 3+ pilots launched with clear metrics showing product value Technical close plan established for every active enterprise opportunity Core sales collateral built: demo script, ROI calculator, integration overview, security FAQ Strong working relationship with engineering and a clear process for escalating customer needs At least 2 deals closed where your technical work was critical to winning Who You Are 2 to 5 years of experience as a software engineer or full stack engineer, ideally at a high‑growth B2B company You have built and shipped real products end to end, not just scripts or one‑off integrations Strong foundation in full stack development, APIs, webhooks, and system architecture You are an engineer who actually wants to talk to customers and are curious about sales and product, excited to flex into those areas over time High agency, you proactively identify problems and figure out solutions without being told how Comfortable with ambiguity and moving fast in an environment where the playbook does not exist yet Willing to experiment with new ways of working as AI rapidly changes how companies operate, you do not cling to a fixed process Excited about traveling on‑site to customer locations and being embedded in their world Scrappy and gritty, you have had to figure things out from scratch before and thrived doing it 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 #J-18808-Ljbffr Hyperscale