- Kuala Lumpur, Kuala Lumpur Kuala Lumpur WP Kuala Lumpur Malaysia
Lokasi Kerja
Penerangan Kerja
Tanggungjawab
We are a fintech building internal AI-powered research tools for equities. We are looking for an AI Engineer who can move fast, own technical work end-to-end, build useful tools independently, and use AI as a serious productivity multiplier.
This role is ideal for someone who has already built and shipped multiple projects on their own — not just followed tutorials — and who enjoys turning messy research workflows into reliable software tools used in real trading and investment workflows.
Work arrangementWorking hours: 1:00 PM – 9:00 PM
Fully onsite role
Full-time role
You will design and build AI-assisted research tools for our trading and investment workflows, such as:
Tools that help analyze market data, company information, filings, news, and trading signals
AI research assistants for summarizing, comparing, and extracting insights from financial data
Internal dashboards, scripts, and workflows for faster idea generation and validation
Agentic tools that automate repetitive research tasks
Prototypes and production-ready systems that connect LLMs with databases, APIs, documents, and internal trading infrastructure
Evaluation systems to test whether AI outputs are useful, accurate, and reliable
Own features and tools from problem definition to working implementation
Build working prototypes quickly and turn the best prototypes into reliable internal products
Use LLMs and AI coding tools effectively to speed up development
Connect AI models with real data sources, APIs, databases, and internal tools
Design simple, usable interfaces for research workflows
Write clean, maintainable code that other team members can understand and extend
Debug independently and solve problems without needing step-by-step guidance
Research new AI tools, frameworks, and model capabilities, then apply them pragmatically
Document what you build, explain trade-offs clearly, and maintain the systems you ship
Help define engineering standards, evaluation methods, and reusable infrastructure for AI research tools
Strong evidence of self-directed building: personal projects, tools, apps, bots, automations, open-source work, shipped prototypes, or production systems
Comfortable building full-stack or end-to-end tools independently
Strong Python and/or TypeScript/JavaScript skills
Experience using AI tools heavily in real workflows, such as ChatGPT, Claude, Cursor, Windsurf, Copilot, or similar
Ability to learn quickly, figure things out, and work with ambiguity
Good product sense: you care whether a tool is actually useful, not just technically impressive
Interest in fintech, trading, markets, investing, or data-heavy research workflows
Ability to take ownership, prioritize well, and ship without constant supervision
Experience with LLM APIs, agent frameworks, RAG, embeddings, evals, or tool-calling
Experience with data engineering, SQL, databases, or analytics workflows
Experience scraping, parsing, or structuring messy web/document data
Experience with financial data, trading systems, backtesting, or market research
Experience building internal tools, dashboards, browser extensions, bots, or automation scripts
Familiarity with Git, deployment, cloud platforms, and API integrations
Experience taking a prototype into production or maintaining tools used by real users
Someone who only has classroom experience and no independent projects
Someone who waits for detailed instructions before starting
Someone who uses AI casually but has not learned how to use it deeply for building
Someone who writes code but does not think about user workflow or product usefulness
Someone who needs a highly structured corporate environment to be productive
You might be a great fit if you:
Have a portfolio of tools or projects you built because you wanted them to exist
Use AI every day to code, research, debug, design, and learn
Can take a vague problem like “make our research process faster” and turn it into a working prototype
Are curious about how financial markets work
Enjoy working in a small, fast-moving startup environment
Prefer building and shipping over long theoretical discussions
Want ownership over important internal tools, not just isolated tickets
AI tool to summarize company filings and highlight trading-relevant changes
Research assistant that compares multiple stocks using structured financial and market data
Internal chatbot that queries our research notes, backtests, and trading documentation
Tool that turns an investment hypothesis into a checklist, data pull, and validation workflow
News and catalyst monitoring system for selected U.S. equities
AI-assisted factor research workflow for generating, testing, and documenting ideas
Internal agent system that automates recurring research and monitoring workflows
Please include:
Links to 2–3 projects you built yourself
A short explanation of what you built, why you built it, and what technical decisions you made
A short note on how you use AI tools in your development workflow
Any experience or interest you have in fintech, trading, investing, or data-heavy research
Examples of projects or systems where you took ownership from idea to shipped result
We care much more about evidence of building ability than credentials.
Peringatan Penting
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