Why Offshore AI Engineers and Forward Deployed Engineers Are the Next Competitive Edge for Modern Enterprises

A good friend who is also CFO of a high-growth company bought me coffee a few months ago and it was one of the most enjoyable and riveting conversations that I've had in a while. We're all swimming/drowning in the AI revolution, and I'm sure many of us are feeling like we're not doing enough. Separately, everybody is being asked to incorporate more AI into their professional workflows... but many don't seem to have fully been able to contextualize what this really means - if they're able to measure output gains and productivity gains in their jobs when thought through holistically. This coffee meeting was like no other such conversation that I've had in the past...

We had a full hour-long conversation on how this high-tech company CFO is being faced with so much internal resistance to AI adoption.

He shared that only a third of the entire company was ready to adopt AI, another third was 'meh' on AI, and the last third was completely against AI (many afraid that it would lead to losing their jobs). Every board meeting, the big topic of conversation was the adoption of AI internally, The CFO took it upon himself to be the AI advocate within the company.

Fast forward today, 90% of his entire company is leveraging AI in an Enterprise setting to drive a much higher work product because of the automation of agentic workflows that they are able to drive within their specific line of business.

The biggest unlock was to hire a set of offshore AI Engineers who helped spin up these agents for the business users. These AI Engineers sat down with every single line of business leader within this company, understood the repetitive, monotonous, and tedious workflows, and then built AI agents, AI workflow automation, and AI applications to on their internal enterprise system (in their case, it was ). This raised the entire AI maturity curve within their company.

As an example, my CFO buddy automated their entire contract review cycle where every new contract that he had to sign would be checked against an existing contract with existing terms, compare price increases, deviations from standard legal language or previously approved terms, check usage rates and calculations against their telemetry systems, check payment terms, and any other critical components that needed to be reviewed prior to signing off on the contract. He went through ~4 contract reviews every week, which took him at least two and a half hours per contract. Now he is able to get through these contracts in under 10 minutes.

That's 9+ hours of time savings for a C-Suite exec.

He also shared another example of and Agent build by these offshore AI Engineers for his CRO counterpart. Being a Bay Area company, they knew that leaders within their core prospect ICP are all somehow connected internally to the employees and leaders within their own company, whether first- or second-degree connection. If the AI engineer could somehow integrate existing ICP list, target persona, data from Salesforce and their data lake, get info from Apollo and Linkedin Sales navigator to understand a social connection map, and then build draft emails for the respective AEs to drive 10-15 warm introductions daily, that could be quite game-changing.

They have now built over 95 internal applications!

Obviously, this conversation got me excited and gave me the opportunity to leverage the infrastructure that we've built at Exordiom Talent to recruit experienced offshore talent that can perform these types tasks for prospects and clients that want to adopt AI internally to drive efficiency in work outputs - ultimately increase their AI Maturity.

👉 If you're looking for someone who can do this for you at your company, just intake your requirements here and we'll immediately get you plugged in!

The AI Engineer and the Forward Deployed Engineer is quickly becoming one of the most critical hires in modern companies. Unlike traditional engineers who focus on building products, AI Engineers and the FDEs specialize in applying large language models (LLMs), automation frameworks, and AI agents to business operations.

According to McKinsey, as much as 40% of tasks across business functions can be automated with AI by 2030 (McKinsey). That means finance, HR, operations, legal, customer support, marketing, and sales teams will all see workflows reshaped.

Yet AI talent remains scarce — and prohibitively expensive. In the U.S., AI Engineers often command $250K–$500K+ annually, a figure that puts them out of reach for most growth-stage companies.

For functional leaders across departments, AI Engineers and FDEs are becoming force multipliers. Their work goes beyond experimenting with models — it directly accelerates productivity:

• Finance: Automating reconciliations, forecasting models, and expense categorization
• HR: Streamlining recruiting pipelines, resume screening, and onboarding workflows
• Customer Support: Deploying AI chatbots with human escalation to improve response times
• Marketing: Building agents to test messaging, enrich data, and scale personalization
• Legal & Compliance: Drafting standard contracts and automating compliance checks
• RevOps & SalesOps: Reducing manual CRM work, automating reporting, and qualifying leads
• Sales: Automating research, finding common patterns and connections, and deal acceleration

In short, AI Engineers unlock internal productivity at scale, enabling every department to focus on higher-value work.

Hiring an AI Engineer or a Forward Deployed Engineer doesn’t have to mean burning $500K of budget. Offshore AI Engineers provide the same applied skill sets at a fraction of the cost.

• Cost savings: Offshore AI Engineers are available at 1/10th of the US-employee cost
• Speed: Roles can be filled in under a few weeks, versus 6mo+ for U.S. hires
• Capacity: For the cost of one U.S. AI Engineer, companies can hire 10 offshore AI Engineers
• Flexibility: Scale pods of AI Engineers up or down as needs evolve

This approach allows companies to experiment with AI across multiple functions at once — something that’s impossible if budget is tied up in a single high-cost hire.

The ROI of offshore AI Engineers comes from both cost efficiency and speed to impact:

• More experiments: Instead of betting on one hire, companies can test AI use cases across several departments
• Faster validation: With more engineers, ideas get prototyped and deployed in weeks, not quarters
• Embedded execution: Offshore AI Engineers integrate into business teams directly, ensuring automation maps to real workflows and KPIs

Example: For the same $500K that would cover one domestic AI Engineer, a company could hire a handful of offshore AI Engineers to do the following and still save $300k+

1. Automate financial reporting workflows
2. Build a recruiting pipeline agent for HR
3. Deploy a customer support routing bot with human handoff
4. Build multiple sales agents to drive research based pipegen
5. Build a contract compare agent
6. Build a legal bot for deal review

.... and endless other impactful apps for the LOB leaders.

This multiplies the impact across the enterprise instead of concentrating it in one silo.

Simply put, its exciting! It's super exciting to hear about how the modern leaders are finding opportunities to elevate their work. They want to spend time doing things that are massively impactful. I recently watched a video by Jensen Huang , who refutes the common misconception that AI will eliminate jobs. Instead, he explains that AI will automate tedious tasks, freeing us HUMANS to generate new ideas and innovate. Far from making us obsolete, this shift enables us to create more opportunities and ultimately become even more productive in our work.

We at Exordiom Talent are evolving to meet this demand by recruiting talented offshore AI Engineers and Forward Deployed Engineers who embed directly into business teams. These are not theoretical researchers — they are applied practitioners vetted for their ability to deliver automation and efficiency inside functional workflows.

Our mission is to make it possible for every functional leader — from CFOs to CHROs to CROs — to leverage AI Engineers as a force multiplier for productivity.

AI adoption is no longer isolated to product teams. It’s moving into every line of business. Leaders who bring in AI Engineers now will out-iterate competitors, cut costs, and accelerate output across the enterprise.

And with offshore AI Engineers, this no longer requires $500K bets. For a fraction of the cost of one high-priced U.S. hire, companies can activate AI across finance, HR, support, marketing, and revenue — all at once.

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