
Johnny Tran
@baots
Lead Engineering at Miss Money Penny who built a production RAG platform and cut LLM-layer latency by 10–20%.
What I'm looking for
At Miss Money Penny, I own the architecture and delivery of a production RAG platform for customer-submitted insurance documents and internal knowledge bases. I built its document-to-answer pipeline, including query routing and insurance-specific entity extraction, and reduced LLM-layer latency by 10–20% through prompt and context optimization, caching, and request batching.
At Amanotes, I developed BigQuery and Dataflow pipelines that prepared game-event data for recommendation systems, and built subscription and revenue-reconciliation flows. Earlier, I delivered features for TRUCKONNECT and backend APIs for Blueplate Hong Kong; my AI projects include a real-time eKYC solution that placed second in the Data4Life national competition and is used in production identity verification.
Experience
Work history, roles, and key accomplishments
Senior AI Engineer & Technical Lead
Miss Money Penny
Oct 2021 - Present (4 years 11 months)
Lead AI engineering for a GDPR-regulated insurance and financial services platform, owning the architecture and delivery of the company's RAG stack alongside core backend and cloud infrastructure.
Senior Backend & AI Engineer
Amanotes
Nov 2019 - Oct 2021 (1 year 11 months)
Built the backend and data platform underpinning subscription monetization and analytics for a portfolio of globally distributed music games.
Senior Full-Stack Developer
Mitsubishi FUSO Truck and Bus Corporation
Jan 2017 - Oct 2019 (2 years 9 months)
Delivered features and refactoring for TRUCKONNECT, a connected-vehicle telematics platform for commercial fleet operators, working in a distributed Japan–India engineering organization.
Education
Degrees, certifications, and relevant coursework
University of Greenwich
Bachelor of Science (Honours), Computing
Grade: Upper Second-Class Honours (2:1)
Bachelor of Science (Honours) in Computing with Upper Second-Class Honours (2:1).
Tech stack
Software and tools used professionally
OpenAPI
Amazon EC2
Google Cloud Platform
Amazon CloudWatch
Amazon S3
Kubernetes
Docker Compose
Amazon CloudFront
MySQL
PostgreSQL
MongoDB
Django
Bootstrap
Google Analytics
Redis
Python
Flask
FastAPI
Linux
Milvus
AWS Lambda
Amazon RDS
pytest
Amazon Cognito
Git
Docker
Apache Beam
SQL
Azure Blob Storage
Qdrant
LangChain
Ollama
Weaviate
ChromaDB
OpenAI API
Anthropic Claude API
Google Gemini API
Llama.cpp
Faiss
LM Studio
PEFT
Sentence Transformers
AWS
Availability
Location
Authorized to work in
Salary expectations
Social media
Job categories
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