May. 20, 2026
17 minutes read
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Seventy-two percent of employers worldwide say they can’t find the talent they need right now, and for the first time, AI model and application development has overtaken traditional engineering as the hardest skill set to hire for. That’s the backdrop betting and iGaming operators are building against — in an industry where being first to launch in a newly regulated market is often the difference between owning a customer base and fighting for scraps of one.
Most operators facing this pressure default to one of two options: hire in-house, or bring in a niche iGaming development shop. Both have a structural weakness this article will name directly. Nearshore development — specifically nearshore teams with deep banking, payments, and enterprise engineering backgrounds — solves a problem neither of the standard options fully addresses: getting a platform built fast, by engineers who already operate at the compliance and security standard regulated betting increasingly requires, without the multi-month hiring cycle or the architectural lock-in that come with the alternatives.
Betting and iGaming are one of the more starkly time-sensitive verticals in software. A new jurisdiction opens — a US state legalizes mobile sports wagering, a Latin American market finalizes its regulatory framework, an EU country liberalizes online casino — and the operators who launch first capture a customer base before their competitors are even live. This isn’t true of most software categories, where a few months of delay costs market share gradually. In betting, a slow launch can mean ceding an entire market’s early adopters to whoever got there first.
The global online gambling market is projected to reach $120.35 billion in 2026, growing to $211.99 billion by 2031 — that growth is disproportionately concentrated in newly regulating markets, which is exactly where the first-mover advantage matters most and where an operator’s build timeline gets tested hardest.
Being second to market doesn’t just mean smaller market share — it means competing against an incumbent that already has player data, brand recognition, and payment relationships established in that market. The cost of a slow build compounds well past the launch date itself, which is what makes the hiring bottleneck described in the next section such an outsized business risk rather than just an operational inconvenience.
Modern betting platforms need engineers who can combine real-time systems architecture, payments engineering, fraud and risk modeling, and regulatory compliance literacy — a combination that’s rare even before accounting for the fact that betting operators are competing with fintech companies and big tech for the same talent pool. ManpowerGroup’s 2026 Global Talent Shortage Survey found that 72% of employers globally report difficulty finding the skilled talent they need, and for the first time, AI model and application development has overtaken traditional engineering roles as the hardest capability to hire for worldwide — meaning the exact profile betting platforms need most is also the profile every other industry is competing hardest to hire.
BLS projects software developer, QA analyst, and tester employment to grow 15% from 2024 to 2034 — much faster than the average occupation — with roughly 129,200 openings projected each year. That growth in demand isn’t matched by an equivalent growth in supply, and it shows up directly in hiring timelines.
Walking through what a specialized in-house hire actually looks like makes the problem concrete. Weeks one and two typically go to writing and posting the role, since a job description for “real-time fraud engineer with payments experience” doesn’t pull from a standard template. Weeks three through six are spent sourcing and screening, and specialized candidates in this profile are fielding multiple competing offers from fintech and big tech, which stretches decision timelines further. Weeks seven and eight usually involve final-round interviews, offer negotiation, and a notice period at the candidate’s current employer. By the time a single specialized hire starts, two months have often passed — and a fraud engineer, a payments engineer, and a compliance-literate backend developer means running that cycle three times in parallel, competing against each other for the same limited candidate pool. A licensing window measured in weeks doesn’t survive that math.
Under time pressure, in-house hiring teams often default to whoever’s available rather than whoever’s right for the role. Generalist engineers are faster to find than specialists in fraud modeling or payments architecture, which means teams built under a launch deadline frequently end up thin in exactly the areas — compliance, security, real-time risk scoring — that matter most for a regulated betting platform’s long-term stability.
The market is full of vendors purpose-built for iGaming — odds engines, RNG casino games, turnkey sportsbook platforms, live-dealer integrations. Many are genuinely strong at gaming-specific product features and can get a recognizable betting product live quickly.
Few of these vendors have deep, hands-on experience with the banking-grade compliance, fraud detection, and payments engineering that regulated betting platforms increasingly need as they scale into multiple jurisdictions. Gaming-specific expertise and financial-services-grade engineering discipline are different skill sets, and most vendors in this space have built the former without the latter.
Turnkey and white-label platforms trade long-term flexibility for short-term speed. They’re genuinely fast to launch, but operators building on them are boxed into the vendor’s architecture — differentiating the product or expanding into a new market’s specific compliance requirements often means working around the platform’s constraints rather than building for them directly.
This is where the actual differentiator comes into focus: a nearshore team with genuine enterprise and banking-grade engineering experience combines the compliance and security depth a betting operator increasingly needs with the flexibility of a dedicated build team — something neither in-house hiring under time pressure nor a niche iGaming vendor cleanly offers.
Betting and iGaming platforms aren’t built once and left alone — fraud patterns evolve, live-betting traffic spikes around major events, and compliance requirements shift as an operator enters new markets. This kind of iterative, incident-driven work benefits enormously from a development team working in the same or adjacent timezone as the operator’s core market, which is exactly what nearshore Latin American teams offer relative to offshore alternatives on the other side of the globe.
Coderio’s own engineering centers — Buenos Aires, Medellín, Lima, Santiago, Mexico City, and Montevideo — span time zones from UTC-3 to UTC-6, meaning a US or European operator’s engineering team is online and collaborating in real time during core business hours, not working around an eight-to-twelve-hour gap that forces everything into asynchronous handoffs.
When something breaks during a major match or a peak betting window, the difference between a team nine time zones away and one working the same business hours is the difference between a same-day fix and a next-day one. For a platform where a production issue during a live event has immediate revenue consequences, that gap matters far more than it would for most software categories.
Nearshore delivery also reduces the communication friction commonly associated with offshore development — shared working hours, closer cultural alignment, and easier real-time collaboration — without the cost premium that comes with fully domestic hiring.
Cost savings from nearshore LatAm engineering are real, and any operator evaluating this model should expect them — that part isn’t in dispute and doesn’t need to be oversold. But cost efficiency is table stakes at this point, not a differentiator; nearly every nearshore vendor in the market leads with a savings percentage, which means it’s the wrong basis for choosing a partner in a regulated, high-stakes vertical like betting.
The better question isn’t “how much cheaper,” it’s “what does the same budget buy.” A generalist nearshore vendor and a nearshore team with genuine banking and payments engineering pedigree can carry similar hourly rates while producing very different outcomes on the parts of a betting platform that actually carry risk — fraud detection, compliance architecture, payment reliability. For an operator weighing that decision, the cost savings are the same either way; the engineering discipline behind the build is not.
The advantage here isn’t just fintech-specific experience — it’s a broader engineering pedigree built across banking, payments, and other regulated, high-stakes industries. Coderio’s client roster spans Visa, IBM, Coca-Cola, FedEx, Santander, BBVA, and other Fortune 500 names, and the common thread across that list isn’t the industry vertical — it’s the standard of engineering discipline those clients demand.
F500 clients bring rigorous SLAs, exacting security review processes, scale requirements most vendors never encounter, and formal change-management discipline. Engineering teams that have delivered under those conditions arrive at a betting or iGaming engagement already conditioned to that level of scrutiny, rather than needing to develop it for the first time under a regulator’s or a payment partner’s watch.
This isn’t an abstract claim. Coderio’s companion pieces on banking-grade fraud and bot detection for online betting and on balancing instant payouts against fraud risk lay out the specific technical architecture this experience produces — real-time risk scoring, tiered verification, and payments infrastructure built the same way Coderio has built it for banking and trading clients like OANDA and dLocal.
Coderio’s approach treats security and compliance as an architectural starting point rather than a pre-launch checklist — audit trails, access controls, and encrypted data handling built into the system from the first line of code, not retrofitted once a regulator asks for evidence. This is the same “audit-ready by construction” principle covered in the companion fraud-detection article’s discussion of ISO 27001 readiness.
For betting operators specifically, this matters more than in most industries because multi-jurisdiction licensing, AML obligations, and payment-partner underwriting all effectively audit the engineering itself, not just the policy documents around it. Coderio’s Digital Security Studio and Security Audits practices build exactly the control environments regulators and payment partners expect to see before they’ll underwrite an operator’s expansion into a new market.
Coderio’s experience taking Fortune 500 clients through AI readiness — assessing and modernizing legacy systems, data infrastructure, and architecture so they can actually support AI workloads, not just running a readiness assessment and stopping there — combined with production AI deployment beyond prototyping, transfers directly to where betting and iGaming operators are already investing: fraud and bot detection models, personalization engines, and predictive models for responsible-gambling early warning. Betting platforms carrying the same legacy technical debt any established enterprise accumulates need that modernization work done first, before a fraud model or personalization engine has clean, real-time data to actually run on — a step most iGaming-focused vendors skip past because they’re used to building on greenfield or turnkey platforms rather than modernizing an existing one. This connects directly to the ManpowerGroup finding that AI model and application development is now the single hardest skill set to hire for globally — the operators who can access that full readiness-through-deployment capability through an established partner rather than competing for scarce in-house AI talent have a real structural advantage.
This differentiator isn’t limited to what Coderio builds for clients, either. Engineers who use AI development tools fluently in their own daily workflow — for code generation, review, and testing — ship measurably faster than those who don’t, which is increasingly a hiring filter in its own right rather than a nice-to-have. A nearshore partner worth evaluating should be able to speak to all three: modernizing the systems AI needs to run on, implementing AI models for the client’s product, and AI-tool fluency inside the engineering team actually doing the building.
Most iGaming-focused development shops can build gaming features competently but haven’t operated AI systems at the governance and scale standards Fortune 500 clients require — ongoing model monitoring, data governance, and responsible-deployment practices that regulated industries increasingly expect as standard, not optional.
Applied to betting specifically, this experience is what makes it possible to build fraud-detection models that keep improving as fraud patterns evolve, personalization engines that respect regulatory limits on engagement, and predictive models that flag at-risk gambling behavior early enough to matter — all areas where the underlying AI governance discipline matters as much as the model itself.
Coderio’s team assembly model is built to directly counter the multi-month in-house hiring timeline described earlier. Days one and two cover role scoping — defining the specific technical needs of the engagement against the engineering bench, not writing a generic job description from scratch. Days three through five cover shortlist assembly and technical screening, pulled from an existing vetted bench rather than a cold search, which is the step that collapses weeks of a typical hiring cycle into days. Days six and seven cover final alignment and onboarding, with a start date typically inside that seven-day window. Set against the two-month-plus timeline for a single specialized in-house hire described earlier, this isn’t a marginal improvement — it’s a different category of speed entirely.
Nearshore engagements are also structured to scale as a platform’s needs change — a larger team during initial build, a leaner team focused on live-ops and incident response once the platform is stable, and the ability to scale back up quickly when an operator expands into a new jurisdiction. This flexibility matters most at exactly the moments described at the start of this article: a new market opening, a compliance deadline, or a competitor’s launch, where the ability to staff up quickly is itself the competitive advantage.
Before evaluating specific criteria, it’s worth being clear on the engagement model itself, since “nearshore team” gets used loosely. Staff augmentation embeds nearshore engineers directly into an operator’s existing team and processes — the right fit when an operator already has technical leadership in place and needs to fill specific skill gaps. A dedicated team model instead gives the operator a self-contained nearshore team with its own technical leadership, better suited to a full platform build or a distinct new product line. Most engagements land on some blend of the two, shifting emphasis as the project moves from initial build toward steady-state operations.
With that distinction in mind, the criteria that matter most:
Nearshore development means working with a team in a similar or adjacent timezone — for US and European operators, this typically means Latin America. Offshore development usually means a much larger timezone gap, which slows down iterative work and incident response specifically, even when the technical quality is comparable.
With an established partner and a pre-vetted engineering bench, team assembly can happen in as little as seven days from kickoff to start date — compared to the two months or more a typical in-house specialized hiring process takes per role.
Yes, provided the team has genuine experience with regulated, compliance-heavy industries. Teams with banking and payments backgrounds specifically are well positioned here, since AML, KYC, and audit-trail requirements in betting closely mirror what those teams have already built for financial institutions.
It depends on what’s being compared. A turnkey platform is often cheaper and faster for an initial launch, but trades away architectural control and flexibility. A nearshore build gives an operator a platform they own and can adapt as they expand, which usually pays off once an operator needs to differentiate or scale into new markets.
Betting platforms require frequent production support around live events, fraud pattern updates, and compliance changes — all work that benefits from real-time collaboration. A same-timezone team can resolve a live incident the same day; a team on the opposite side of the globe often can’t respond until the next business day.
Real-time systems architecture, payments engineering, fraud and risk modeling, regulatory compliance experience, and increasingly, AI implementation experience for fraud detection and personalization use cases — the same combination of skills covered throughout this article.
Yes, this is one of the structural advantages over a fixed in-house headcount — a well-structured nearshore engagement can scale team size up for a new market launch and back down once that market stabilizes, without a full renegotiation each time.
Teams with genuine fintech and banking backgrounds do — this is the core differentiator this article argues for. Real-money payment systems in betting require the same transactional integrity, fraud detection, and compliance discipline as banking and trading platforms, which is exactly the experience a fintech-background nearshore team already has.
Staff augmentation embeds nearshore engineers into an operator’s existing team and technical leadership, ideal for filling specific skill gaps. A dedicated team model provides a self-contained team with its own technical leadership, better suited to a full platform build. Many engagements use both models at different stages of the same project.
The operators moving fastest into new betting and iGaming markets aren’t choosing nearshore development because it’s cheaper — they’re choosing it because it’s the only option that combines hiring speed, timezone-aligned production support, and genuine enterprise-grade compliance and security experience in one team. In-house hiring can’t move fast enough under a licensing deadline, and niche iGaming vendors rarely bring the banking-grade engineering discipline that regulated betting increasingly requires.
That combination is exactly what Coderio brings to a betting or iGaming engagement: a 7-day team assembly process, a track record built serving Fortune 500 clients across banking, payments, and other regulated industries, a security-by-design approach that treats compliance as an architectural starting point, and AI implementation experience that transfers directly into fraud detection and personalization use cases betting operators are already investing in. As the market for AI and specialized engineering talent gets tighter industry-wide, that combination becomes less of a nice-to-have and more of the deciding factor in who launches first.
If your betting or iGaming platform needs to move fast without cutting corners on compliance and security, talk to Coderio about assembling your nearshore engineering team in as little as seven days.
As Chief Growth Officer, Fred leads Coderio’s strategic growth initiatives, driving revenue acceleration through enterprise client relationships, high-impact partnerships, and tight alignment between sales, marketing, and client success. Fred brings a rare combination of strategic depth and operational execution built across some of the world’s most demanding organizations. He has held executive roles at Snowflake, VMware, and Broadcom, leading commercial strategy, enterprise sales operations, and customer portfolio management at scale. Earlier in his career, he served as a Managing Consultant in Strategy and Transformation at IBM, and as Executive Vice President and Regional CFO at CRH. Before his corporate career, Fred served as a Captain in the United States Army.
As Chief Growth Officer, Fred leads Coderio’s strategic growth initiatives, driving revenue acceleration through enterprise client relationships, high-impact partnerships, and tight alignment between sales, marketing, and client success. Fred brings a rare combination of strategic depth and operational execution built across some of the world’s most demanding organizations. He has held executive roles at Snowflake, VMware, and Broadcom, leading commercial strategy, enterprise sales operations, and customer portfolio management at scale. Earlier in his career, he served as a Managing Consultant in Strategy and Transformation at IBM, and as Executive Vice President and Regional CFO at CRH. Before his corporate career, Fred served as a Captain in the United States Army.
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