AI Workflow Intelligence Scale-Up (London) - Xist4
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AI Workflow Intelligence Scale-Up (London)

Sourcing a Senior Full-Stack Engineer to Scale an AI-Native Workflow Insights Platform for Enterprise Growth



The Challenge

Our client was a fast-growing London SaaS scale-up that had just closed a Series B round. Their platform helped large enterprises understand, optimise, and automate complex operational workflows across compliance, finance, customer operations, and risk. The engineering challenge was significant: the platform needed to move from supporting dozens of enterprise teams to hundreds of global customers, each requiring secure, scalable, real-time workflow intelligence.

To get there, they needed a Senior Full-Stack Engineer with deep experience across Typescript, React, AWS serverless technologies, and event-driven architecture. Someone who could work across the full stack, contribute to product direction, and design infrastructure capable of handling high-volume workflow analytics in regulated environments. That combination is not easy to find. Engineers with genuine cloud-native depth and a product mindset who have also delivered at enterprise scale are in short supply, and most of them are not looking.

The leadership team also needed an honest view of the market before scaling the engineering organisation. Compensation benchmarks, talent availability, and stack alignment all needed to be understood before outreach began.

The Solution

Xist4 ran a research-led retained search, starting with a structured market review before any candidates were approached.

  • Worked with the CTO and Product Lead to define the full technical and product profile: Typescript, React, Material UI, AWS Lambda, EventBridge, DynamoDB, Hasura, Postgres, SST, CDK, and end-to-end feature ownership.
  • Profiled over 150 senior engineers with experience in cloud-native platforms, workflow automation, event-driven systems, and AI-backed enterprise SaaS, covering salary bands, talent availability, stack alignment, and competitor hiring activity.
  • Targeted engineers from scale-ups in process intelligence, workflow automation, and operational analytics, positioning the company as a place where senior engineers have real ownership and influence over core systems.
  • Conducted structured technical interviews evaluating system design, event-driven architecture capability, and cloud-native decision-making, assessing product thinking and collaboration alongside technical depth.
  • Shared weekly market intelligence on candidate supply, salary expectations, response rates, and how the role was landing in the market, giving the leadership team the information they needed to adjust their approach in real time.

The Result

Within seven and a half weeks, Xist4 presented a shortlist of senior full-stack engineers with strong hands-on experience across the client’s exact stack.

The appointed candidate had previously scaled workflow and analytics features at a well-known enterprise SaaS vendor. They brought direct expertise across SST, CDK, DynamoDB, Lambda, Postgres, and React, and quickly took ownership of the workflow ingestion engine. Within the first quarter, the engineering team reported measurable improvements in shipping velocity, stronger feature reliability, and a more scalable foundation for the platform’s next stage of growth. For a business moving from early traction to enterprise-grade scale, that is exactly the hire that needed to land well.

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