Caylent Expanded Engineering Workforce Model
The firm increased its forward deployed engineering staff to 125 employees.
Updated on Oct. 10, 2026 in Employment
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Caylent has grown its team of 125 forward deployed engineers to support specialized software development workflows. This model helped client Smarsh achieve significant operational improvements through generative AI integration.
Why it matters
The shift toward embedded engineering teams reflects a growing corporate reliance on external specialists to overhaul internal software development lifecycles. By integrating AI tools directly into workflows, companies are looking to accelerate productivity and reduce technical debt.
Smarsh reported a 30 percent increase in test coverage and saved $10 million in capacity over one year. Caylent currently employs 125 forward deployed engineers and plans to transition 200 more into the role.
The players
Caylent
Caylent is an Irvine-based company that operates as an Amazon Web Services Premier Partner and maintains a dedicated Anthropic consulting business unit.
Smarsh
Smarsh is a technology firm that partnered with Caylent to transform its software development processes using generative AI.
The details
Caylent partnered with Smarsh and Amazon Web Services to embed Claude Code into the Smarsh development lifecycle. These forward deployed engineers integrate directly into client workflows to rebuild operating models and improve software quality.
Timeline
The findings were reported in October 2026.
Macro View
The story follows the pattern set by the industry-wide adoption of AI-augmented software development lifecycles in its shift toward specialized engineering models. This movement contrasts with traditional staffing models by prioritizing deep integration of AI tools into core development tasks.
Companies adopting these embedded engineering models may see reduced wait times for software updates and improved product stability. However, businesses should monitor whether these high-cost consulting models provide long-term budget predictability compared to internal hiring.
The takeaway
The success of embedding specialized engineers into workflows demonstrates how generative AI can significantly reduce defect rates and operational costs. Organizations should evaluate if their current development teams have the necessary AI training to replicate these productivity gains.
Further reading
Find more local updates on the Employment page.
Source note: This article includes information reported by CRN.
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