Automated Investment Research System Development

AI Systems Engineer — Audit-Grade Investment Research Platform (Indian Equities)
We are building an autonomous, institutional-grade “Investment Committee” system for Indian equities (NSE/BSE).
This is NOT a trading bot and NOT a dashboard project. It is a backend-first, audit-grade research platform designed to perform forensic-level analysis of company filings, fundamentals, governance, and supply-chain signals.
The system must operate with ZERO manual data handling and full traceability.
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Core Objective
Design and implement a fully automated, multi-agent research platform that:
• Discovers, ingests, validates, and parses official exchange filings
• Enforces evidence-based decision logic in backend code
• Maintains cryptographically verifiable audit trails
• Supports human approval ONLY for final buy/sell decisions
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Key Technical Requirements (Non-Negotiable)
• ZERO manual operations (no uploads, no extraction, no human data handling)
• Logic-gated Supervisor with hardcoded BUY rules in Python (not prompts)
• Strict evidence hierarchy (Concall = supporting only, never BUY trigger)
• Secure fallback with domain allow-lists, SHA256 checks, timestamp validation
• ISIN-first identity mapping with versioned, hashed document storage
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Expected Technology Stack
• Python (advanced backend)
• LangGraph (stateful multi-agent systems)
• Pydantic / schema enforcement
• LlamaParse or equivalent document parsers
• PostgreSQL
• Vector databases (Pinecone / Chroma / FAISS)
• Indian market data APIs (NSE/BSE, Zerodha, etc.)
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Professional Standards
This is an institutional-grade research system designed to run “lights-out.”
Any proposal involving manual data handling or scraping will not be considered.
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Candidate Profile
We are seeking a Backend Systems Architect or Quantitative Data Engineer with experience in financial data pipelines, compliance-grade logging, and production AI orchestration.
If your background is primarily UI dashboards, scraping, or prompt engineering, this project is unlikely to be a good fit.
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Evaluation
Shortlisted candidates may be asked to complete a short technical PoC demonstrating automated PDF ingestion, hashing, and validation.
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How to Apply
Please include:
1. Relevant past projects
2. High-level technical approach
3. Fixed-price quote
4. Estimated timeline (weeks) Show More