When release schedules slip, the instinct is to hire faster. This client discovered that sending more CVs without refining the brief only deepened the problem. Together, we redesigned how contract and permanent talent entered their delivery teams — including a Gen AI pod that needed RAG, evaluation, and MCP integrations alongside core platform engineers.
The company — a product engineering and managed services provider serving banking, retail, and industrial software clients — had secured three major programmes in a single quarter. Delivery leads were already stretched. Attrition among mid-level engineers was climbing. Temporary contractors were arriving without enough context to contribute within the first two sprints.
Leadership faced a familiar dilemma: protect margins by staffing quickly, or protect reputation by holding out for the perfect profile. Neither extreme was viable. What they needed was a staffing model aligned with how their delivery pods actually functioned.
What was not working - Job descriptions listed tools rather than outcomes — so candidates appeared qualified on paper but underperformed in context. - Multiple hiring managers briefed agencies inconsistently, creating mismatched expectations and wasted interview cycles. - Contractors were onboarded like permanent employees, delaying productive contribution by weeks. - Bench and surge planning happened after the win, not before — so capacity always lagged behind demand.
How Halcer partnered We started with the work, not the vacancy. With delivery leads and HR, we mapped three role families carrying the most programme risk: full-stack engineers for product pods, QA automation specialists for release reliability, and cloud/DevOps profiles for environment stability.
For each family we defined success at 30, 60, and 90 days — what "good" looked like in stand-ups, code reviews, and client demos. Those definitions became the filter for every shortlist.