AI Solutions and Capabilities

Role Overview

Sigma Nova Science develops foundation model architectures for complex scientific domain applications. We are transitioning our core research assets into scalable, commercial AI capabilities that enterprise clients can evaluate, operate, and buy.

In this role, you will lead the bridging work between research initiatives and early client opportunities. You will frame capability definitions, scope client demonstrators, structure upstream technical validations, and package solutions. Operating with high autonomy and agility, you will co-construct offerings alongside cross-functional teams (R&D, Strategy, Partnerships, Ops) and collaborate directly with the CEO to shape early offer positioning and strategic roadmap priorities.

Role Focus & Collaborative Alignment

• Core Focus & Framing: You lead capability definition, solution specifications, offering packaging, pricing options, and demonstrator design.
• Cross-Functional Co-Construction: You partner continuously with Partnerships & GTM on client feedback and account expansion, Research & Tech Dev on reusability and feasibility, Strategy on value propositions and market alignment, and Programs & Operations on tracking and milestone delivery.
• CEO Collaboration: You work directly with the CEO—engaging in strategic and scientific brainstorming—to align on pricing recommendations, domain sequencing, and collaborative project commitments.

Key Responsibilities

AI Capabilities & Offer Definition (30%)

• Productization & Structuring: Translate abstract research assets and codebase components into modular, functional capabilities.

• Qualification & Sequencing: Define qualification criteria (data availability, partner engagement, ROI, timeline) to prioritize exploration across domains.

• Packaging & Pricing: Build capability specifications, licensing ideas, and pricing proposals alongside Strategy and IP counsel for executive review.

• Reusability Audits: Partner with Research & Tech Dev to distinguish core platform building blocks from custom client work.

  Demonstrators & Technical Validation (25%)

• Validation Protocols: Define scope, success criteria, and test protocols for client demonstrators based on strategy use-case dossiers.

• Rapid Prototyping: Build lightweight proofpoints and fast prototypes (including vibe coding) to test technical hypotheses quickly.

• Feedback Loops: Lead test-learn-pivot cycles on demonstrator outcomes to continuously refine offer specifications.

  Upstream GTM & Technical Account Reference (25%)

• Technical Pre-Sales: Assess client data maturity, evaluate data processing complexity, and structure technical expansion pathways for enterprise accounts.

• Proposal Delivery: Draft technical sections of client proposals and execute feasibility sign-offs prior to external commitments.

• Field Intelligence: Gather field objections, client needs, and reuse signals to inform central product and technical planning.

Discovery & Ecosystem (20%)

• Frontier Scanning: Track scientific literature and emerging AI developments to keep the company aligned with state-of-the-art research.
• Collaborative Projects: Represent the company in industrial/academic consortia and contribute technical sections to French and European grant proposals.
• Exploratory Outreach: Engage technical stakeholders in new domains to build long-term pipeline opportunities.- Experience: 7–8+ years operating at the intersection of AI research, deep-tech engineering, and commercial solutions strategy.
• Scientific & Technical Depth: Advanced degree or equivalent depth in science/engineering; ability to engage as an intellectual peer with PhD/HDR-level scientific leaders and research teams.
• Solutions & Value Framing: Strong instincts for translating abstract technical codebases into customer-facing capabilities with clear ROI.
• Hands-On Technical Ability: Comfortable prototyping, writing code, and conducting technical feasibility evaluations directly.- Recruiter prescreen
• Business/Product discussion
• Onsite interview (brainstorming, culture fit..)