Build an AI research engine grounded in investment judgment The opportunity

Algo One is hiring a hands-on researcher and builder to develop an AI-powered investment research engine, working closely with our leadership team. The aim is to turn financial information into well-reasoned investment hypotheses, test those hypotheses, and improve the research process through systematic feedback.

You will combine investing knowledge, practical coding ability and independent thinking. You will help translate experienced investors’ reasoning into repeatable AI workflows, while challenging weak assumptions and checking whether the resulting research is actually useful. The scope includes Indian and global equities, including businesses that cannot be understood through straightforward profitability screens.

What you will do

- Build and operate AI-assisted research workflows: source discovery, document ingestion, financial analysis, company and sector research, thesis development, counterarguments and ongoing monitoring.
- Work directly with our leadership team to understand their investment frameworks. Turn feedback on research outputs into explicit research criteria, examples, reusable instructions and evaluation tests; track whether each change improves results.
- Read filings, financial statements, earnings calls, industry material and economic data. Identify what matters, reconcile conflicting evidence, and separate facts from assumptions and interpretation.
- Use frontier models, APIs and practical code to prototype and automate research. Choose tools for their usefulness and reliability, and explain trade-offs in accuracy, speed and cost.
- Produce concise investment memos with a clear thesis, valuation logic, catalysts, downside risks, disconfirming evidence and source references. Surface uncertainty and the questions that still need investigation.
- Create reproducible research and evaluation records. Help design paper portfolios and historical tests that account for information availability,



transaction costs and bias, with human review before any live deployment.
- Identify significant market developments and research themes for audience-facing videos and commentary. Explain why a development matters in language a thoughtful non-specialist can understand.

What you will bring

- Sound understanding of finance, investing and economics, demonstrated through your reasoning and work. You can read financial statements, discuss business quality and valuation, and connect economic developments to company outcomes.
- Strong analytical judgment and intellectual curiosity. You ask precise questions, distinguish signal from noise, look for evidence against your thesis, and change your view when the facts change.
- Practical ability to write, understand, test and debug code, preferably Python, and work with structured data and APIs. AI coding tools are welcome; you must be able to explain and verify what they produce.
- Hands-on familiarity with modern AI tools and a serious desire to build with them. You understand that a convincing answer can still be wrong and can design checks for unsupported claims and numerical errors.

How you work

- You take ownership of an open-ended problem, turn it into concrete experiments and deliver useful progress without waiting for detailed instructions.
- You contribute your own ideas and respectfully challenge the team when the evidence points elsewhere. You can explain both your conclusion and how you reached it.
- You read widely, learn quickly and stay close to developments in markets and AI. You are willing to discard an approach that fails testing.




- You communicate clearly and respond reliably. You can support time-sensitive research across market hours, with availability expectations agreed explicitly.
- You treat source quality, confidential information and data permissions seriously. You build traceable research and preserve a clear boundary between research output and authorized investment action.

Experience and background

There is no minimum years-of-experience requirement. Early-career candidates and self-taught builders are welcome if they can demonstrate strong investing judgment, learning ability and practical execution. We value evidence of your work more than a polished CV or a particular degree.

Useful evidence could include an investment memo, a research automation project, a working AI tool, a thoughtfully analysed paper portfolio, or an independent research project. Experience with financial data, retrieval systems, agent workflows, statistics or backtesting is helpful, but you do not need to have done all of these.

What success looks like The initial goal is a research engine that produces useful, verifiable work and improves through feedback. Early milestones will include:

- A clearly scoped research workflow, a small set of representative investment questions and a documented standard for judging output quality.
- An end-to-end prototype that produces source-linked research on a focused company universe, handles missing or conflicting information, and makes its limitations visible.
- A repeatable evaluation process comparing AI-assisted work with a simple baseline and human review, tracking factual accuracy, research usefulness, turnaround time and cost.
- A usable research process that supports investment discussion and selected content themes, with documented failure modes and a prioritized plan for improvement.

How to apply

Please submit your CV in PDF format. No work samples or other supporting material are required at this stage.

📌 AI Investment Research Builder (India)
🏢 Algo One AI
📍 India