GTV Digital Technology Application Review for EP– MC + OC2 + OC3

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Hi everyone,

Background: I’m a Senior Software Engineer with 5+ years of experience, primarily across frontend/backend (full-stack) engineering, digital products, analytics & experimentation and, more recently AI/MCP. I work as a Senior Software Engineer with Company A, a San Francisco-based technology company, through Company B (sub-contractor). I’m also building Shop Everywhere an MCP-powered conversational commerce product.

Criteria: MC + OC2 + OC3

MC evidence:

  • Published research paper on conversational commerce using MCP-enabled AI assistants — published in GJETA, with a registered DOI and public publication page.
  • Winner of “Most Innovative Use of AI” at an internal company hackathon — evidence of the project, award/recognition and my individual contribution.
  • Senior Software Engineer recognition/remuneration evidence — employment/contract evidence, salary documentation and market benchmarking demonstrating senior-level standing.

OC2 evidence:

  • Speaker at Cursor Community Lagos (May 2026) — delivered a technical talk on “Building an MCP Server and Integrating with ChatGPT”, with event photographs, presentation material and public/event evidence with over 600 participants.
  • Published technical article on Model Context Protocol (MCP) — Medium publication with analytics showing views/readership and engagement.
  • Technical thought leadership on LinkedIn around MCP/AI development — posts/articles with impressions, reposts, comments and engagement from software professionals.
  • Shop Everywhere Product — GitHub project demonstrating practical MCP implementation and contribution to the wider developer ecosystem. (Currently strengthening external usage/engagement evidence)

OC3 evidence:

  • Company A US/UK Domain Consolidation — significant engineering contribution to consolidating the UK platform into companya.com/uk, including architecture, localisation, SEO, analytics and infrastructure changes.
  • Optimizely experimentation work — implemented product experiments contributing to approximately 20% improvement in signup/retention-related outcomes, supported by experiment/dashboard evidence.
  • Single GTM + GA4 analytics architecture — consolidated separate US/UK analytics implementations, introduced locale tracking and improved consistency/accuracy of analytics across the platform.
  • Shopify/Elevar e-commerce analytics integration — technical contribution across checkout/purchase event tracking and ecommerce analytics.
  • Supporting evidence includes architecture diagrams, dashboards/metrics and confirmation of my individual contribution from senior leadership.

Three referees:

  • Head of Engineering — worked directly with me and can speak to my technical contributions and impact.
  • Senior technology leader from a previous organisation — direct knowledge of my engineering work and career progression.
  • Senior technology professional from a previous organisation — Also direct knowledge of my work and contributions over the required period.

I’d really appreciate feedback from anyone experienced with the Digital Technology Global Talent route, particularly around whether MC + OC2 + OC3 is the strongest combination for this profile and whether any of the evidence above should be moved between criteria.

Any feedback on the weaker parts would be greatly appreciated.

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MC is the weakest part of this pack and needs rebuilding. Internal company awards are explicitly excluded by the Guide, so the hackathon piece won’t count no matter how it’s framed. A paper in a low-impact journal published close to application timing also risks triggering the Guide’s flag about evidence produced solely to support timing. Salary alone is also insufficient unless paired with clear impact beyond day-to-day work. Strong MC evidence usually looks like main-stage talks at sector-leading events, externally validated awards, or coverage in major trade publications.

OC2 has a structural issue. The Guide is explicit that self-published articles on LinkedIn or Medium are not considered sufficient evidence, which removes two of the four pieces immediately. Shop Everywhere is also risky here because OC2 requires voluntary activity not undertaken whilst representing a company or its products; a personal commercial product doesn’t fit. The Cursor Community talk can work if the 600 figure is attendees rather than registrations and the event is recognised as sector-leading. Stronger OC2 evidence usually means OSS contributions to established projects with public metrics, or structured mentorship through a recognised programme.

OC3 is the strongest of the three but leans heavily on internal engineering wins. Domain consolidation, GA4 setup, and Shopify integration read as doing the job well rather than contributing to the wider sector. The experimentation piece with measurable business impact carries the weight; the others need external framing, or an employer letter that attributes commercial outcomes to your individual work rather than the team’s. Being sub-contracted through Company B also complicates attribution, so the pack should clearly establish Company A as a product-led digital technology business.

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