Forward Deployed Solutions Engineer

Mission

Every consumer on earth purchases in one of three places: online, big-box retail, or mom-and-pop shops. Paradoxically, the largest commercial channel is, by far, humble traditional trade shops. Yet they remain fragmented, offline, and opaque.

Native is the first intelligence-grade system built to penetrate this opacity. Each analog store is digitized into a dynamic graph where noise is filtered into low latency signals, transforming the antiquated offline world into advanced digital intelligence. Commercial leaders gain the precision to see what others cannot, store by store, rendering decisive decision advantage to win the market.

Join the ground floor of the only platform engineered to decode the analog economy into operational dominance.

Talent Values

• High Leverage: Consistent ability to attain the productive capacity of 5-10 people through grit, raw talent, and sheer force of will.
  

• High Agency: Relentless sense of ownership in the outcome, regardless of circumstance, acting decisively to shape the environment rather than being shaped by it.

• Curiosity With Discipline: An evidence seeking, measurement mindset without succumbing to analysis paralysis, and a penchant for experimentation.

• Intellectual Honesty: Certain enough to act, humble enough to always be learning
  

Role

Native is hiring a Forward Deployed Solutions Engineer to sit between Solutions Engineering, customer systems, applied analytics, and deployment.

This is not a demo role. It is not a support role. It is not a post-sale implementation function. The role exists to make complex enterprise customers understand exactly how Native fits into their operating environment, why it matters, what it will require, and how it will create measurable leverage.

In the sales motion, this person creates technical conviction. They lead discovery, demos, solution mapping, proof design, objection handling, integration scoping, and deployment planning in partnership with Account Executives. In strategic accounts, they move closer to the customer environment: data platforms, APIs, internal systems, reporting layers, workflow logic, operating constraints, and implementation risk.

The role is deliberately positioned between technical selling and forward-deployed execution. Native does not need a presales specialist who stops at the demo. Native needs a technical-commercial operator who can help win the deal and then stay close enough to ensure the solution survives contact with the customer’s systems, data, workflows, and field reality.

The customer environment is usually fragmented. Data is distributed across warehouses, BI layers, ERP systems, CRM systems, field tools, retail execution platforms, spreadsheets, internal reporting, and local operating processes. Workflows are often undocumented. Models and reporting structures are often disconnected from the decisions they are supposed to support. Native’s opportunity is to become the intelligence and execution layer across that environment.

That requires advanced analytics fluency, modeling judgment, systems thinking, and integration literacy. This person must understand how customer data is structured, exposed, governed, joined, analyzed, and operationalized. They must be able to reason about data quality, measurement design, model outputs, prioritization logic, API dependencies, implementation constraints, and the practical path from technical possibility to deployed value.

The standard is precision. If a technical objection slows the deal, isolate the real issue. If the customer cannot see how Native connects to its systems, map the connection. If the deployment path is unclear, define it. If a workflow is poorly understood, document it. If the model logic is not credible, pressure-test it. If the AE needs technical force to advance the account, provide it.

Performance is assessed on one axis: the ability to convert technical credibility into revenue progression, and revenue progression into durable customer value.

Core Responsibilities

• Own Technical Conviction:  Lead the technical dimension of enterprise sales cycles. Run discovery, demos, workshops, solution mapping, proof design, validation, objection handling, and deployment scoping. The goal is not product explanation. The goal is buyer confidence that Native can operate inside the customer’s environment and improve how decisions get made.
  

• Partner With Sales to Close Revenue:  Work directly with Account Executives to advance complex opportunities. Understand account strategy, buyer dynamics, decision criteria, technical risk, urgency, competitive pressure, and the moments where technical clarity determines whether a deal progresses or stalls. The role carries variable compensation because the work is directly tied to revenue creation.
  

• Map Native Into Customer Architecture:  Understand how Native connects to the systems customers already use: data warehouses, BI tools, ERP, CRM, retail execution platforms, field applications, reporting layers, APIs, internal models, and workflow systems. The work must show where Native fits, what it replaces, what it strengthens, and what it needs to integrate with.
  

• Apply Advanced Analytics and Modeling Judgment:  Bring credibility to conversations involving measurement design, data interpretation, model outputs, prioritization frameworks, exception detection, segmentation, forecasting, and operational analytics. Help customers understand what Native can measure, what it can infer, where confidence is high, where assumptions matter, and how analytics translate into action.
  
• Shape API and Integration Paths:  Identify integration requirements, API dependencies, authentication constraints, data exchange patterns, payload structures, mapping logic, governance issues, and implementation risks early in the sales process. The work must reduce ambiguity before the contract is signed, not discover preventable complexity after it.
  

• Make Native a Force Multiplier:  Identify where Native can strengthen existing customer workflows across commercial planning, store prioritization, retail execution, distributor management, field force productivity, issue detection, performance management, executive reporting, and market measurement. The platform should not sit beside the workflow. It should increase the output of the workflow.
  
• Operate Fractionally Forward Deployed:  Move deeper into strategic customer environments when the account requires it. Diagnose system constraints, data realities, workflow gaps, field complexity, and implementation risk. Shape deployment strategy, support implementation design, and help convert signed contracts into measurable operating value.
  

• Build the Technical Proof System:  Create the assets required to win sophisticated buyers: technical demos, integration maps, solution architectures, workflow diagrams, proof-of-value designs, analytics examples, model logic explanations, deployment narratives, technical explainers, and customer-specific materials for executive, commercial, and technical stakeholders.
  

Competencies

• Advanced Analytics and Modeling Fluency: Clear experience with analytics, modeling, measurement design, data interpretation, and the translation of complex data into business action. Must be able to reason about data quality, model outputs, scoring or prioritization logic, predictive frameworks, analytical tradeoffs, and operational value.
  

• Technical Seller: Demonstrated ability to support complex enterprise sales cycles through technical discovery, solution design, demos, proof design, validation, objection handling, and buyer education. Must understand that technical work in a sales process exists to advance revenue.
  

• Forward-Deployed Range: Able to move beyond presales into customer deployment context. Must be capable of understanding workflows, systems, data realities, field constraints, implementation risks, analytics requirements, and operational value creation inside strategic accounts.
  

• Systems Thinking: Able to see how Native can become a force multiplier across customer workflows and the platforms that support them. Must understand that the value of the platform is not only in what it shows, but in how it changes decisions, prioritization, execution, measurement, and operating cadence.
  

• Commercial Judgment:  Understands how enterprise deals move. Able to partner tightly with Account Executives, read buyer dynamics, identify risk, create urgency, support pricing confidence, and contribute directly to closed-won revenue. Must be comfortable with variable compensation tied to sales impact.
  

• Product-to-Customer Translation: Able to turn Native’s product architecture into customer-specific understanding. Must explain not only what the platform does, but how it changes the customer’s ability to see stores, measure execution, understand market reality, connect intelligence to existing systems, and act with greater precision.
  

• Executive Presence:  Able to build trust with senior commercial and technical leaders while staying grounded in operational reality. The role requires comfort in executive conversations, technical architecture discussions, field workflow analysis, and deployment planning.
  

Technical Requirements

• Customer Systems and Data Platform Depth:  Experience working with enterprise data environments, business systems, data platforms, BI tools, APIs, reporting layers, analytics workflows, and workflow platforms. Must understand how customers structure, govern, move, expose, and operationalize data across systems.
  

• Advanced SQL for Cloud Data Warehouses: Demonstrated fluency writing and optimizing analytical SQL against modern cloud warehouses such as Google BigQuery. Must be able to reason about query cost, performance, and data volume.
  

• API and Integration Judgment: Familiarity with API engineering, integration design, data exchange, system interoperability, authentication, payload structure, data mapping, implementation constraints, and technical troubleshooting. Must be credible enough to diagnose integration realities, ask precise questions, and shape workable paths with customers and internal teams.
  

• Integration Patterns: Familiarity with the patterns that move data between systems and the judgment to choose the right one for the customer's constraints.
  

Company

Headquartered in New York City, Native is a high-growth, venture-backed company redefining how physical retail is measured, understood, and acted on. Backed by Vista Equity Partners, a $100B+ platform focused on enterprise systems that own workflows, proprietary data, and execution, its mandate is clear: equip commercial leaders with the intelligence layer required to win, decisively.

Native replaces static research and fragmented fieldwork with  living intelligence subscriptions —where agentic AI orchestrates continuous data collection, and reasoning  across the market. The result is not a market analyzed after the fact, but one that is continuously seen, understood, and actioned  in real time, enabling its users with an unfair competitive advantage.

Location

Mexico City