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NEXTMOVEFDE careers · United States

Forward Deployed Engineering Manager

Technologies

Python · SQL · LLMs · ML · Salesforce · Retool

About Actively AI

SaaS platform deploying per-account AI agents that research accounts and surface revenue opportunities 24/7 for enterprise sales teams.

Series B · 50–200 people

Job description

The full responsibilities and requirements are on the employer’s site.

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Source and classification

Production engineering · Evidence for this classification:

hands-on with customers. Onboarding involves data integration (connecting to their Salesforce, transforming their data into our standardized format), configuration, often a 1-month pilot where we iterate to prove ROI, and ongoing iteration post-conversion. We run discovery to deeply understand each customer’s business, build product capabilities tailored to their workflows, and explore new use cases alongside them. This has been working great, with a high conversion rate from qualified pilot to paying customer, and we typically pay for ourselves multiple times over in the pilot alone. But it takes serious hands-on work, and today our small, mighty, and growing FDE team is running these engagements. We're looking for a player-coach to lead this function. You'll personally own our most strategic deployments while hiring, mentoring, and building the playbooks and tooling that let us
More from the job description

About Actively AI Actively AI is defining a new category: Intelligence-Led Revenue. Revenue organizations have always been bottlenecked on human capacity. Reps triage which accounts get attention. Context disappears at every handoff. On any given day, the vast majority of accounts have exactly zero people thinking about them. Actively addresses this at the structural level. Our platform deploys Per-Account AgentsTM across our customers’ TAM, working 24/7 to research, identify opportunities, and advance next steps without being asked. Leading enterprises including Ramp, Ironclad, and Samsara are already making this shift. Our co-founders are former Stanford AI researchers, and the team comes from Harvard, CMU, Berkeley, Brex, Scale AI, and Google. We've raised $68M from TCV, First Harmonic, Bain Capital Ventures, First Round Capital, and more. About the Role We're extremely hands-on with customers. Onboarding involves data integration (connecting to their Salesforce, transforming their data into our standardized format), configuration, often a 1-month pilot where we iterate to prove ROI, and ongoing iteration post-conversion. We run discovery to deeply understand each customer’s business, build product capabilities tailored to their workflows, and explore new use cases alongside them. This has been working great, with a high conversion rate from qualified pilot to paying [... source excerpt omitted ...] alone. But it takes serious hands-on work, and today our small, mighty, and growing FDE team is running these engagements. We're looking for a player-coach to lead this function. You'll personally own our most strategic deployments while hiring, mentoring, and building the playbooks and tooling that let us scale this motion 5-10x. This is explicitly not a hands-off management role. You'll be in the data, on customer calls, and shipping code roughly half your time. The other half is making everyone around you better and turning artisanal work into a repeatable system. Day in the Life You'll operate as a blend of: An FDE – personally leading 1-2 strategic deployments so you [... source excerpt omitted ...] what your team feels An engineering manager – hiring, coaching, and setting the bar for technical and customer excellence A founder – extreme ownership over deployment velocity, customer outcomes, and team health A PM – turning patterns from deployments into product defaults and internal tooling, so each deployment is easier than the last A GTM partner – shaping which customers we take on, how pilots are scoped, and how we hand off to long-term success Who You Are You've done the IC job and were great at it. Former FDE, customer-facing product engineer, or founder-operator who personally onboarded early customers. Strong Python and SQL, ML fundamentals, real interest or exp

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