Case Study: Sopra Steria - Hiring

AI Innovation

INDUSTRY: IT Services & Consulting

Sopra Steria: Designing a Scalable Talent Acquisition System

AI-POWERED

Recruitment at scale

Sector: IT Services & Cybersecurity

LAYERED

Candidate persona model

Challenge: Hiring scarce technical talent (AI developers, cybersecurity, DevOps)

SCALABLE

Talent acquisition system

Project: AI-powered candidate persona platform and recruitment content system

Context
Sopra Steria was recruiting in highly competitive areas including AI, cybersecurity, and DevOps. With multiple specialties, seniority levels, and geographies in play, the ambition was to make hiring more precise, responsive, and scalable.

Reframe
Rather than optimising campaigns, we shifted the focus from advertising vacancies to engaging distinct technical audiences. In a highly competitive market for scarce technical talent, differentiation depends on speaking directly to the motivations, expectations, and career stage of each candidate group.

Solution
We built a dynamic candidate persona architecture combined with an AI-powered content engine. The system generates tailored recruitment messaging by specialty and seniority while maintaining brand consistency.

Innovation
A layered data model combines motivations, technical domain, and career stage to generate persona insight dynamically. This enables scalable variation without manual persona creation.

The Impact

Recruitment shifted from campaign-by-campaign execution to a scalable, self-service system the team can operate independently. The platform increased speed, precision, and relevance while positioning Sopra Steria as a more competitive employer in high-demand technical markets, attracting better quality candidates.

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Sopra Steria was competing for AI, cybersecurity, and DevOps talent in a highly competitive market. Recruitment followed a traditional vacancy-led approach, which limited differentiation across roles and seniority levels.

We worked with Sopra Steria to build a structured persona model and AI-supported content system that generates tailored recruitment messaging by specialty and career stage. The result was a repeatable framework the internal team can use to produce relevant, role-specific content at scale.

Sopra Steria delivers complex technology programs for enterprise clients. Talent availability is directly linked to delivery timelines, client satisfaction, and revenue continuity.

The strategic opportunity was to strengthen hiring capability in highly competitive skill areas – particularly AI, cybersecurity, and DevOps – by increasing relevance and speed without expanding marketing headcount.

The ambition was to build long-term recruitment infrastructure.

The initial focus was on improving recruitment campaigns.

The broader opportunity was to shift from marketing vacancies to engaging with people, understanding technical professionals as distinct decision-makers with different motivations depending on career stage and specialty.

Rather than optimise a handful of priority roles, the decision was to design a system capable of supporting all role combinations across campaigns and years.

We designed a flexible persona model that adapts by specialty, seniority, and career motivation, enabling Sopra Steria to engage distinct technical audiences rather than advertising generic roles.

The employer brand remained consistent, but its expression shifted depending on who was being recruited; mentorship for graduates, autonomy for architects, leadership scope for senior specialists.

On top of this, we built an AI-powered content engine that generates tailored job ads and recruitment messaging based on role context.

AI handled scale and variation while human strategy defined positioning and guardrails.

Recruitment content moved from manual drafting to system-driven generation.

We approached candidate personas the same way we approach buyer personas: understanding their decision context, motivations, and evaluation criteria.

We built a layered architecture that combines motivation, specialty, and seniority, enabling the system to generate accurate persona insights across combinations without manual creation.

The project transformed recruitment marketing from a vacancy-led process into a structured, candidate-centric system. This process previously required manual handling is now managed through a single data model.

The introduction of AI templates expanded how the marketing team uses automation within recruitment, embedding AI directly into day-to-day campaign execution.

By enabling more precise and responsive candidate marketing, the platform strengthened Sopra Steria’s ability to compete for scarce technical talent.

More importantly, Sopra Steria now has a structured way to understand and engage different technical audiences. Recruitment shifted from producing individual campaigns to operating through a repeatable system that the internal team can run themselves.

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