Building a Future-Ready Graduate Talent Strategy in an AI Disrupted Hiring Market

Discover how Draup helped turn AI disruption and campus data into smarter graduate hiring.

~30,000

Employee Count

~$4.9B

Revenue

Telecom Software & Technology Services

Industry

Chesterfield, Missouri, USA

Headquarters

About the Company

The organization is a global leader in software and technology services for the communications and media industry, serving the world's largest service providers across revenue management, network operations, and digital transformation. Operating in over 85 countries with more than 30,000 employees and annual revenues exceeding $4.5 billion, it sits at the intersection of enterprise technology and industry-wide transformation. As 5G, cloud-native infrastructure, and AI reshape the communications landscape, the organization has made building a future-ready workforce — particularly at the graduate level — a strategic priority.

The Core Challenges

Entry-Level Demand Collapse

Entry-level tech hiring had declined sharply since 2022, with global job postings down approximately 63% from peak. The organization needed a structured view of which roles were most affected and whether the trend was cyclical or structural.

Role Transformation Ambiguity

The workloads of Software Development Engineers, QA Engineers, and DevOps professionals were being reshaped by AI — but the precise shift from automated to augmented to human-led tasks was not well mapped, making it difficult to calibrate graduate expectations and onboarding programs.

Campus Hiring Intelligence

The organization lacked a consolidated, data-backed view of hiring volumes, placement patterns, and recruiter trends across Tier 1 and Tier 2 B-schools in India — making it difficult to prioritize campus investment and identify which institutes offered the best talent-to-cost fit for different functional needs.

Employer Category Position

The organization had limited visibility into its hiring presence relative to peers — including IT services firms, Big Tech, hyperscalers, and telecom software competitors across both Tier 1 and Tier 2 campuses, making it difficult to identify strategic whitespace for early campus engagement.

The Solution

DevOps Engineer

PROFILE

LOCATION ANALYSIS

TALENT MARKET INSIGHTS

CAREER PATHS

TECH STACK

The image is for representational purpose only.

Hiring Trend & Market Intelligence

Mapped the structural shift in entry-level tech hiring across the U.S., UK, Germany, India, and France — with job postings still 50% below early-2022 peaks. India’s top IT services firms recorded a 20-year low in fresh graduate intake, with two of the largest pausing campus placements entirely. Of active tech roles, 53% now explicitly require AI skills. Profiled the fastest-growing emerging roles — Prompt Engineer (~300% demand growth in two years), AI/ML Engineer, Cybersecurity Analyst, and GRC Analyst.

Role-Level Workload Transformation

Delivered a granular workload transformation map across five core early-career engineering roles — SDE, Test and QA Engineer, DevOps Engineer, Systems Engineer, and AI/ML Engineer — distinguishing AI-automated tasks from AI-augmented responsibilities and human-led work. With AI now generating 30–60% of routine code at major tech firms, the entry-level SDE role is shifting from code writing toward reviewing, refining, and validating AI outputs. Regression execution and test case creation have shifted substantially to AI for Test Engineers, with the human role moving up the value chain.

Campus Hiring Landscape Mapping

Mapped placement volumes, top domains, prominent roles, leading recruiters, and hiring locations across all 51 institutes. Nearly half of Tier 1 placement offers are concentrated among the top IIMs and ISB — with the leading three institutes recording 870, 590, and 576 offers respectively. Among Tier 2 institutes, the top three led placements at average CTCs of INR 12–18 LPA, offering meaningful cost leverage for high-volume operational and analytics hiring.

Employer Category Intelligence

Assessed campus hiring intensity across four employer categories: IT Services firms (very high presence), Big Tech (selective and declining), Hyperscalers (under 2% of disclosed MBA offers at Tier 1 campuses in 2024), and telecom software peers (fewer than five recorded MBA hires across Tier 1 institutes). This limited peer presence in management pipelines was identified as a clear first-mover opportunity for the organization.

Outcome

Structured Market Intelligence

The organization gained a data-backed view of where early-career tech demand is contracting, where it is growing, and how AI is reshaping the composition of graduate hiring across functions and geographies — enabling more targeted campus strategy decisions.

Role Transformation Roadmap

Detailed workload-level transformation maps for each core engineering role gave the organization a clear framework for recalibrating graduate job descriptions, onboarding programs, and early-career expectations to reflect AI-augmented delivery models.

Tiered Campus Prioritization Framework

The organization gained a data-backed view of where to direct campus investment by tier, institute, domain, and cost band — enabling a differentiated strategy that uses Tier 2 institutes for cost-efficient operational and analytics hiring and Tier 1 institutes for leadership and high-impact strategy roles.

Strategic Whitespace Identification

Employer category intelligence confirmed that telecom software peers have negligible campus presence at both Tier 1 and Tier 2 institutes — identifying a clear first-mover opportunity to build brand recognition, initiate pre-placement engagement, and develop management talent pipelines ahead of competitors.

Powered by unparalleled global labor & market data

26K+

Skills

1B+

Professionals

5700+

Locations

1.6M+

Peer Group Companies

1B+

Job Descriptions

4M+

Career Paths

Data Trust & Methodology at Draup

Draup uses a structured methodology to reduce inaccuracies and prevent misleading information, with a focus on transparency and responsible data practices.

1

Data Transparency and Coverage

Draup sources data from diverse, vetted global inputs including public datasets, labor information, professional ecosystems, and industry research. Coverage varies by region and role, and we supplement limited areas with alternative sources and analyst-led modeling.

2

Profiles Behind the Numbers

All aggregate insights related to buyers, roles, skills, and locations are grounded in structured, anonymized human and organizational profiles rather than pure extrapolation. This ensures context, reliability, and protection of personal identities.

3

Data Hygiene and Integrity

We maintain a clean, accurate data environment by removing duplicates, outdated entities, and invalid records. Automated checks powered by ML models and analyst reviews work together to ensure clarity and accuracy for every entity, such as buyer, role, skill, technology, or company. Learn more

4

AI Governance and Bias Mitigation

Our governance framework combines automated evaluations with Human-in-the-Loop reviews. We use statistical checks, audits, and cross-source comparisons to reduce demographic and structural bias before insights reach the platform.

5

Compensation Guardrails

Compensation insights use blended, directional inputs such as aggregated ranges, benchmarks, modeled distributions, and market signals. We distinguish clearly between modeled and reported data and apply guardrails to prevent over-interpretation.

6

Hourly and Frontline Workforce Coverage

For hourly, frontline, and blue-collar roles where digital visibility is limited, we incorporate government datasets, localized labor information, and specialized partners to build a more complete and balanced view of workforce supply and demand.