AI-First Sales Enablement Operator

Storm Ideas•,

11d•£30,000 - £30,000•Remote

About The Position

This is an AI-first sales enablement role, focused on building and running a conversion engine where AI systems are central. The role involves designing, operating, and continuously improving this engine, which uses AI agents, structured proof, and automation to create sales materials like pitch decks, case studies, proposals, and RFP responses. The goal is to make these materials fast, accurate, consistent, safe, and persuasive, leveraging AI for speed while ensuring human judgment for quality and accuracy. The position requires a deep understanding of the company's services and output, close collaboration with delivery teams, and a genuine engagement with the work produced. The ideal candidate will possess strong agency, judgment, systems thinking, technical-mindedness, and a high learning velocity, with a practical and critical approach to using AI as a capable tool for delegating and refining work.

Requirements

Strong structuring and writing ability, with a talent for turning messy evidence into clear, credible commercial narratives.
An eye for how commercial materials should look: able to make or direct clean, on-brand decks and collateral with AI and design tools.
Evidence of ability to get deep into bespoke services like strategy, social, content, creative production, and AI transformation, with a genuine appetite to understand the work.
Some experience, strong project work, or clear self-started evidence in sales enablement, proposal or bid work, agency or consultancy marketing, content operations, or adjacent work.
Genuine command of AI tools and a strong instinct for how fast the landscape is moving; frontier LLMs and agentic tools already central to your real work.
Evidence of building AI-assisted workflows, template systems, structured libraries, knowledge bases, or automations that someone other than you could use.
Practical understanding of prompt and agent configuration, context design, and lightweight technical systems (e.g., markdown, GitHub, Airtable, document and deck tools), or the demonstrated appetite to learn them fast.
Real judgment about proof: what counts as evidence, what can be claimed, what needs permission, and what would embarrass you if challenged.
Comfort working with senior people, tight deadlines, and live commercial pressure.
Strong written communication, context discipline, and async working habits.
Meaningful overlap with US Pacific working hours.

Nice To Haves

A designer's taste, though not necessarily a designer's skills.

Responsibilities

Build and run Storm's conversion engine as an AI-first system, including structured proof, claims, module libraries, assembly workflows, and QA processes.
Build and maintain the proof library with agent-readable context such as case studies, outcomes, client examples, usage permissions, and confidentiality notes.
Build and maintain the approved claims library, defining what Storm can confidently say and the associated permissions and limitations.
Create and maintain the pitch and proposal module system with reusable, tagged, and current modules for assembly into various sales materials.
Draft and produce case studies from delivery work, account team notes, retrospectives, and client feedback, using AI drafting and human verification.
Assemble tailored pitch decks and proposal outlines for live opportunities, ensuring they are visually sharp, on-brand, and accurate.
Own RFP and procurement readiness, managing company overview, credentials, methodology, team bios, standard answers, and approved language.
Create service one-pagers, offer explainers, and collateral for the AI transformation offer, including diagnostic and workshop materials.
Run the request intake process for sales materials, managing urgency, tracking, and delivery.
Define asset governance, including material storage, approval criteria, naming conventions, versioning, refresh cycles, and archive rules.
Coordinate with account managers and delivery teams to capture proof, outcomes, and examples from ongoing work.
Build QA into every workflow, including claim checks, permission checks, number checks, and confidentiality checks.
Track the performance of the conversion engine, monitoring asset reuse, time-to-draft, proposal turnaround, commercial feedback, and proof gaps.