Portrait of Jimmy Ji

Member of Technical Staff & Co-Founder, ZeroShot

Jimmy Ji

I build AI systems that hold up in production, from real-time speech and translation to secure cloud infrastructure, and help regulated teams adopt AI safely.

Sydney, Australia

Illustration of Live Caption’s translate mode: Chinese speech, English captions.

Expertise

Four areas where I do my best work, usually in combination.

Real-time speech & language AI

Streaming speech recognition, live translation and captions that people can read while the conversation is still happening. I pay attention to latency, to how interim text settles into final captions, and to interfaces that work for people who are Deaf or hard of hearing.

  • Streaming ASR
  • LLM translation
  • Web Audio
  • WebSockets

AI adoption in regulated industries

Bringing AI into organisations where security, audit and compliance come first: clear boundaries on what data may reach a model, testing tools before they reach staff, and training that turns cautious teams into confident users. Much of my experience is in banking.

  • Retrieval-augmented generation
  • MCP tools
  • LLM evaluation
  • Staff training

Back-end services & integration

Java and Spring Boot services where correctness matters, such as payment and remittance messaging, approval flows behind one-time passwords, and encrypted document delivery. I also connect systems through the APIs and workflow tools they already expose.

  • Java
  • Spring Boot
  • REST APIs
  • SQL
  • Workflow automation

Secure cloud & identity infrastructure

Edge-first services on Cloudflare Workers and AWS, and the identity layer underneath them: Microsoft Entra ID, Intune, MFA and conditional access. I design services to hold as little data and as few credentials as they need.

  • Cloudflare Workers
  • Durable Objects
  • AWS
  • Entra ID
  • Intune
  • Docker

How I work

  1. Draw the data boundary first.

    Before choosing a model, decide what must never leave the device or the network. In Live Caption, audio goes straight from the browser to the speech provider and never touches our own servers.

  2. Make progress checkable.

    Milestones are questions with a yes-or-no answer, not percentages someone has to estimate, so progress can be verified rather than argued.

  3. Keep the evidence with the decision.

    Decisions are written down with their sources and confidence. When a claim turns out to be wrong, the record says why, so nobody repeats it.

  4. Know the unit cost before scaling.

    Cost per audio hour, per request or per user is a design input from day one, not a surprise on the invoice.

  5. Use what the platform already offers.

    Most automation comes from mapping the APIs and workflow tools a system already exposes. Custom code fills the gaps.

Case study

Product · Aug 2026 – now · Creator

Live Caption & Translation

Follow the conversation. Take part in your own way.

A browser app that turns speech into readable, shared captions. A host starts captions in Chrome or Edge; others join by QR code or a six-digit code, read along on their own device and reply by typing. It is built for people who are Deaf or hard of hearing, for non-speaking participants, and for conversations across languages.

AwardPeople’s Choice Award, UNSW Founders Peter Farrell Cup 2026. Live Caption powered the live captions in WhoSays’ winning entry.

  1. 01

    Capture

    Microphone or tab audio is captured in the host’s browser.

  2. 02

    Recognise

    Audio streams straight to the speech provider, and captions and translation stream back. Live Caption’s own services never handle audio.

  3. 03

    Share

    Captions are encrypted in the browser and relayed to the room through Cloudflare Workers and Durable Objects.

  4. 04

    Take part

    Participants read along and reply by typing. The host can correct captions and export TXT, Markdown or SRT.

  • A free 30-minute trial needs no account: a separate Workers and D1 service issues temporary keys and enforces daily and per-IP limits.
  • The web app and its server have no third-party runtime dependencies, and tests run in CI before every deploy.
  • JavaScript
  • TypeScript
  • Node.js
  • Web Audio
  • Cloudflare Workers
  • Durable Objects
  • D1
  • GitHub Actions

Talks & workshops

Sessions I run for teams adopting AI. Each takes about an hour and includes live demos.

  • From chat assistants to agents

    How large language models work, what tokens and memory mean in practice, and the step from conversation to agents, together with the data-security rules for using AI at work.

  • Harness engineering: infrastructure for AI agents

    Why the leverage has moved from prompts to context to the harness around a model: persistent memory, tool layers such as MCP, skills and hooks, state, and context compaction. Includes a method for designing reusable skills.

Short bio

Jimmy Ji is a software engineer in Sydney and a co-founder of ZeroShot, an applied AI, data and engineering practice. He builds AI systems that hold up in production, from real-time speech and translation to secure cloud infrastructure, and helps teams in regulated industries adopt AI safely.

His background spans financial-services back-ends, enterprise identity and infrastructure, and AI enablement for staff. He created Live Caption, a browser app that turns speech into shared, translated captions for people who are Deaf or hard of hearing and for conversations across languages. He works in English, Mandarin and Cantonese.

What are you working on?

Send the ZeroShot team a short note about the problem and where things stand. To reach me directly, email hello@jimmyji.dev.