01
About John
Senior Full Stack Engineer with 10 years delivering production ML across LLMs, NLP, and CV. Expert in building performant, responsive frontends (React/Next.js) that interface with RAG systems and fine-tuning pipelines. Deeply experienced in MLOps, optimizing inference from cloud to edge, and enforcing safety/observability for reliable, user-centric AI applications.
Professional profile
- Location
- Philippines
02
Proven on the network
Implementation records and publicly available work, where published.
0 AI Deployments delivered. No publicly identified implementations are available to inspect.
03
What John builds
Implementation domains listed on this profile. Evidence-supported items are identified separately below.
Specialisations
RAG Systems
04
AI Deployments
Real AI implementations demonstrated through evidence.
No publicly identified Deployments are available to inspect.
05
Implementation capabilities
Evidence-supported means linked to a published Deployment or Case Study; other capabilities are Builder declared.
Evidence-supported
No published evidence linked yet.
Builder declared
- RAG Systems
06
Technology
Technologies listed by the Builder, distinguished by published evidence.
Evidence-supported
No published evidence linked yet.
Builder declared
- AWS
- Angular
- Ant Design
- Anthropic Claude
- Astro
- Banana
- Braintrust
- CLIP
- Captions
- Chakra UI
- Claude Code
- Cloudflare
- Cloudflare MCP
- Cosmos DB
- DigitalOcean
- Docker
- Expo
- Flutter
- Framer Motion
- Google Cloud
- HTMX
- Headless UI
- Heroku
- IBM Cloud
- JavaScript
- Material UI
- Next.js
07
Industry experience
Published Deployments support the listed counts. Other industries are Builder declared.
E-Commerce
Builder declared
EdTech
Builder declared
FinTech
Builder declared
IT Services & Systems Integration
Builder declared
Software & SaaS
Builder declared
08
Trust & verification
A closer look at how this profile and its evidence are reviewed.
Community Member
Published evidence is reviewed against the AI Deploy Network Evidence Standard.
How verification works
Verified Builder
Independently reviewed by AI Deploy Labs against the platform Evidence Standard.
How this is verifiedWhat the platform has established, and what remains builder-declared.
- Identity and organisation
- Identity checks confirm that the person presenting this profile controls the account and the professional identifiers attached to it, such as a LinkedIn profile. Organisation membership is confirmed by the organisation, not self-declared by the builder.
- AI Deployments
- An approved AI Deployment is an implementation record the builder submitted and the platform reviewed against the Evidence Standard before publication. Approval confirms the record is complete, coherent and consistent with the supporting material provided — it is not an audit of the client's systems.
- Business outcomes
- Outcome figures are recorded by the builder on the deployment or case study that produced them, and are reviewed at publication. Aggregates shown on this profile are calculated from those approved records only.
- Evidence
- Supporting evidence comes from the records the builder published on this platform: approved AI Deployments, published AI Case Studies, verification outcomes and organisation participation.
- Currency
- Older evidence continues to count and is never removed. Recency is presented separately through Professional Currency so that current expertise can be assessed alongside historical work.
- Traceability
- Every figure on this profile can be followed to the record that produced it. Open the linked AI Deployment or AI Case Study to read the outcome exactly as it was reported.
The platform does not independently audit client systems or financial records. How this is verified
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