Forward Deployed Product Manager, Enterprise

Role Summary

Scale is accelerating the development of AI across the world's most important organizations. The Forward Deployed PM is the person who makes enterprise deployments succeed from the product side — embedded with customers, shaping real production outcomes, and translating messy operational reality into high-signal input for the core platform.

This is not a roadmap PM, a CSM, or a solutions engineer. The FDPM owns product outcomes inside a portfolio of enterprise accounts: earning deep trust with senior customer stakeholders, driving deployments to production, identifying where the product is the bottleneck vs. execution, and feeding durable, specific signal back to the platform team. The best FDPMs have shipped products into large organizations and can tell the difference between a customer's stated request, their actual problem, and what the platform should do.

What You'll Do

• Own product outcomes for our highest impact enterprise accounts. You are the accountable PM for product delivery and customer value.
• Build trusted advisory relationships with VP/C-level buyers and senior technical leads. Become the reliable escalation point on the Scale side before issues surface externally.
• Drive deployments from contract to production. You have done this before for large organizations. You know what 'production-ready' actually means and you close the gap.
• Translate real customer workflows, friction, and priorities into high-signal product input for core platform teams. Not requirements docs — specific, evidence-backed product perspective with tradeoffs articulated.
• Distinguish where the product is the constraint from where execution, integration, or change management is. Drive each type of blocker to resolution through the right channel.
• Partner closely with FDEs so the account runs as a coordinated team, not a set of parallel workstreams.
• Identify and develop expansion opportunities grounded in demonstrated customer value 
• Represent customer reality to platform and leadership with enough credibility that it changes decisions.

What We're Looking For

Core Competencies

• Enterprise deployment ownership: has driven AI/ML or complex software products from contract to production at scale, with real integration, real security constraints, real change management.
• Product judgment in the field: translates customer reality into product direction, not just feature requests; can say no credibly and explain why.
• Customer trust-building: earns and maintains trust with demanding senior stakeholders over multi-quarter engagements; manages conflict without eroding the relationship.
• Technical translation: bridges the gap between customer engineering teams and Scale platform engineers; does not relay messages, adds interpretation.
• Operating in ambiguity: creates structure where there is none; makes decisions with incomplete information; does not wait for fully defined requirements.
• Clear, precise communication: adjusts for audience (exec vs. engineer vs. PM); writes and speaks at the right level of detail; does not over-explain or under-explain.

Must-Have Qualifications

• 6+ years in product management, technical program management, or a customer-facing product ownership role.
• Demonstrated record of shipping products or platform capabilities into large organizations — not pilots or proofs-of-concept. You can name the customer, the scale, the integration, and what production actually looked like.
• Extreme ownership and follow-through: closes loops without reminders, drives outcomes across teams without formal authority, holds self and others to commitments.
• Comfortable operating with senior customer stakeholders (VP/C-level) and senior engineers simultaneously; credible presence in high-stakes rooms on both sides.
• Strong judgment under pressure: makes good calls quickly with incomplete information, knows when to escalate vs. resolve, does not generate thrash.
• Technical fluency sufficient to hold a real conversation with a platform engineer about architectural tradeoffs — not deep coding, but genuine comprehension of how systems work in production.

Preferred Qualifications

• Direct experience with AI/ML platform products — data labeling, RLHF, fine-tuning workflows, or model evaluation pipelines.
• Experience in a startup or early-stage environment where process didn't exist and had to be created.
• Prior forward-deployed or embedded role (consulting, field PM, solutions engineering with ownership).