AI boom sparks rush for engineers who can speak both code and business
Demand for forward deployed engineers is surging as companies move AI projects into production, but talent combining technical depth with domain expertise remains scarce.

- Jun 23, 2026,
- Updated Jun 23, 2026 2:44 PM IST
As artificial intelligence projects move beyond pilots and into enterprise-wide deployment, technology companies are hunting for a rare breed of professional: engineers who can build AI systems, understand the industries they are being deployed in and translate technical capability into business outcomes.
Over the past 12-18 months, demand has risen sharply for forward deployed engineers, or FDEs, who combine deep technical expertise with domain knowledge and commercial understanding. Some estimates suggest demand for FDEs in India has grown 800% year-on-year, although from a negligible base. The role is also advertised under titles such as AI solutions engineer or applied AI engineer.
“As AI is moving from experimentation to implementation, along with technical expertise, employees need to be conversant with engineering teams as well as the business stakeholders,” said Maya Nair, Executive Director with Grafton Recruitment, India.
The requirement reflects a broader change in the AI market. Companies are no longer looking only for people who can build models or write code. They increasingly need professionals who can work with clients, understand their processes, deploy AI in live environments and demonstrate measurable impact.
“What clients are looking for today is not just AI capability, but the ability to integrate AI into business processes and generate measurable outcomes,” said Rajesh Sinha, Founder & Chairman, Fulcrum Digital, an AI-driven IT services firm.
Fulcrum continues to hire data scientists and machine learning engineers, but the growing volume of AI-led work has created demand for customer-facing engineers who can “bridge the gap between technology and business outcomes”. These employees work directly with clients to deploy and optimise AI systems in real-world settings.
The company is seeing demand across enterprise AI transformation, intelligent document processing, customer service automation, knowledge management, software engineering productivity and industry-specific applications in banking, insurance, healthcare, manufacturing and retail.
Coforge is witnessing a similar shift. Addressing an investor conference last month, CEO Sudhir Singh said the company’s talent mix was evolving, with a decline in “pure tech” roles even as demand for FDEs and AI engineers surged. Coforge has more than 20 specialised FDEs and plans to build a pool of about 100 in the coming months. These engineers are typically embedded with clients, where they lead AI deployments and can also generate leads for future projects.
The idea of combining technical and business skills is not new to the IT services industry. What has changed is the centrality of the role as companies attempt to move AI from proof-of-concept projects into core operations.
“While customer-facing engineering roles have existed globally for decades under various titles, the FDE construct has emerged as a distinct role focused on bridging product engineering and customer outcomes,” said Neelabh Shukla, Chief Business Officer, Careernet Group, a talent solutions provider.
“In India, the role is still at a nascent stage but is gaining traction rapidly as enterprises and GCCs accelerate the implementation of AI solutions and seek technical talent capable of not only coding but also driving adoption and business impact,” he added.
Apart from IT services firms and global capability centres, demand is also coming from cloud service providers, AI-native startups and software-as-a-service companies. Most technology companies now have open positions that broadly fit the FDE profile, recruiters said, and hiring is expected to rise as more AI projects enter production.
“As AI becomes embedded into core business operations, companies need professionals who can operate at the intersection of engineering, customer engagement, and business strategy,” said Sinha.
“In the new business landscape, AI deployments require continuous collaboration between technical teams and end users to ensure solutions are accurate, scalable, and aligned with business goals,” said Sinha. “Going forward, I believe organisations will increasingly value professionals who combine technical depth with problem-solving, communication, and domain expertise. The future workforce will not be defined solely by coding ability, but by the ability to translate emerging technologies into tangible business outcomes,” he said.
The problem is that few candidates possess all these skills in one package. Companies are therefore trying to create their own supply by upskilling high-potential employees and giving technical teams more cross-functional exposure.
Fulcrum, for instance, is investing in training that helps technical employees develop a stronger understanding of customer challenges and business objectives. Larsen & Toubro Group IT firm LTM recently announced a new Centre of Excellence under which it plans to develop more than 1,000 engineers in AI skills, including FDEs.
“The role of the technology engineer is evolving rapidly. AI1000 is built to enhance workforce productivity in creating tangible business outcomes,” said Venu Lambu, CEO & Managing Director, LTM. The company plans to create a structured pathway combining technical excellence with domain expertise while preparing employees for future roles.
Such programmes, however, will take time to produce results. In the near term, the industry is struggling to find enough people who can meet the requirements of the job.
“The shortage stems from the profile itself. This isn't a role you can fill with a generalist software engineer or a traditional domain expert alone, as it requires both, in the same person, at a high level of competence,” said Careernet’s Shukla.
The core skill set requires expertise in AI, a strong grounding in data and genuine industry knowledge, a combination that takes years to develop and is not yet being systematically produced by the education system. Recruiters said the bigger challenge is not finding people with technical skills, but finding those who can pair those skills with a strong understanding of business.
“Some organisations are tapping into adjacent talent pools, including solution architects, pre-sales consultants, product managers, and industry specialists who can be upskilled on AI technologies. The focus has become more skill-based, and companies are initiating training internally to be able to grow the talent pools within the organisation to build hybrid capabilities,” said Grafton’s Nair.
Some companies are also creating “pods”, or teams whose members collectively possess the required skills. But experts said this can dilute the original idea of an FDE: a highly skilled individual capable of moving across technology, customer and business domains.
“While there is no shortage of individuals with foundational AI skills, finding talent that can translate AI capabilities into enterprise value remains challenging. The reality is that organisations can no longer rely solely on external hiring. Building AI talent has become just as important as recruiting it,” said Sinha.
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As artificial intelligence projects move beyond pilots and into enterprise-wide deployment, technology companies are hunting for a rare breed of professional: engineers who can build AI systems, understand the industries they are being deployed in and translate technical capability into business outcomes.
Over the past 12-18 months, demand has risen sharply for forward deployed engineers, or FDEs, who combine deep technical expertise with domain knowledge and commercial understanding. Some estimates suggest demand for FDEs in India has grown 800% year-on-year, although from a negligible base. The role is also advertised under titles such as AI solutions engineer or applied AI engineer.
“As AI is moving from experimentation to implementation, along with technical expertise, employees need to be conversant with engineering teams as well as the business stakeholders,” said Maya Nair, Executive Director with Grafton Recruitment, India.
The requirement reflects a broader change in the AI market. Companies are no longer looking only for people who can build models or write code. They increasingly need professionals who can work with clients, understand their processes, deploy AI in live environments and demonstrate measurable impact.
“What clients are looking for today is not just AI capability, but the ability to integrate AI into business processes and generate measurable outcomes,” said Rajesh Sinha, Founder & Chairman, Fulcrum Digital, an AI-driven IT services firm.
Fulcrum continues to hire data scientists and machine learning engineers, but the growing volume of AI-led work has created demand for customer-facing engineers who can “bridge the gap between technology and business outcomes”. These employees work directly with clients to deploy and optimise AI systems in real-world settings.
The company is seeing demand across enterprise AI transformation, intelligent document processing, customer service automation, knowledge management, software engineering productivity and industry-specific applications in banking, insurance, healthcare, manufacturing and retail.
Coforge is witnessing a similar shift. Addressing an investor conference last month, CEO Sudhir Singh said the company’s talent mix was evolving, with a decline in “pure tech” roles even as demand for FDEs and AI engineers surged. Coforge has more than 20 specialised FDEs and plans to build a pool of about 100 in the coming months. These engineers are typically embedded with clients, where they lead AI deployments and can also generate leads for future projects.
The idea of combining technical and business skills is not new to the IT services industry. What has changed is the centrality of the role as companies attempt to move AI from proof-of-concept projects into core operations.
“While customer-facing engineering roles have existed globally for decades under various titles, the FDE construct has emerged as a distinct role focused on bridging product engineering and customer outcomes,” said Neelabh Shukla, Chief Business Officer, Careernet Group, a talent solutions provider.
“In India, the role is still at a nascent stage but is gaining traction rapidly as enterprises and GCCs accelerate the implementation of AI solutions and seek technical talent capable of not only coding but also driving adoption and business impact,” he added.
Apart from IT services firms and global capability centres, demand is also coming from cloud service providers, AI-native startups and software-as-a-service companies. Most technology companies now have open positions that broadly fit the FDE profile, recruiters said, and hiring is expected to rise as more AI projects enter production.
“As AI becomes embedded into core business operations, companies need professionals who can operate at the intersection of engineering, customer engagement, and business strategy,” said Sinha.
“In the new business landscape, AI deployments require continuous collaboration between technical teams and end users to ensure solutions are accurate, scalable, and aligned with business goals,” said Sinha. “Going forward, I believe organisations will increasingly value professionals who combine technical depth with problem-solving, communication, and domain expertise. The future workforce will not be defined solely by coding ability, but by the ability to translate emerging technologies into tangible business outcomes,” he said.
The problem is that few candidates possess all these skills in one package. Companies are therefore trying to create their own supply by upskilling high-potential employees and giving technical teams more cross-functional exposure.
Fulcrum, for instance, is investing in training that helps technical employees develop a stronger understanding of customer challenges and business objectives. Larsen & Toubro Group IT firm LTM recently announced a new Centre of Excellence under which it plans to develop more than 1,000 engineers in AI skills, including FDEs.
“The role of the technology engineer is evolving rapidly. AI1000 is built to enhance workforce productivity in creating tangible business outcomes,” said Venu Lambu, CEO & Managing Director, LTM. The company plans to create a structured pathway combining technical excellence with domain expertise while preparing employees for future roles.
Such programmes, however, will take time to produce results. In the near term, the industry is struggling to find enough people who can meet the requirements of the job.
“The shortage stems from the profile itself. This isn't a role you can fill with a generalist software engineer or a traditional domain expert alone, as it requires both, in the same person, at a high level of competence,” said Careernet’s Shukla.
The core skill set requires expertise in AI, a strong grounding in data and genuine industry knowledge, a combination that takes years to develop and is not yet being systematically produced by the education system. Recruiters said the bigger challenge is not finding people with technical skills, but finding those who can pair those skills with a strong understanding of business.
“Some organisations are tapping into adjacent talent pools, including solution architects, pre-sales consultants, product managers, and industry specialists who can be upskilled on AI technologies. The focus has become more skill-based, and companies are initiating training internally to be able to grow the talent pools within the organisation to build hybrid capabilities,” said Grafton’s Nair.
Some companies are also creating “pods”, or teams whose members collectively possess the required skills. But experts said this can dilute the original idea of an FDE: a highly skilled individual capable of moving across technology, customer and business domains.
“While there is no shortage of individuals with foundational AI skills, finding talent that can translate AI capabilities into enterprise value remains challenging. The reality is that organisations can no longer rely solely on external hiring. Building AI talent has become just as important as recruiting it,” said Sinha.
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