Description :

Key Responsibilities :

Building & Owning the AI Agent Infrastructure :

- Designing and deploying multi-agent systems for investment research, M&A due diligence screening, and FP&A automation using Python and frameworks like LangChain or CrewAI

- Setting up and managing a private cloud environment (AWS or Azure) where all AI workloads run ensuring client data never leaves Tristones controlled environment

- Building and maintaining an internal knowledge base (vector database) that indexes all past project work and makes it searchable by AI agents and analysts

- Integrating AI agents with external financial data sources using controlled API connections with rate limiting and audit logging

- Owning the prompt library : write, test, version-control, and continuously improve the prompts used by all agents

Data Privacy & Security :

- Architect a private LLM deployment self-hosted open-source models or private cloud instances so client data never passes through shared public APIs

- Implementing data classification : tag incoming data by sensitivity and enforce routing rules so confidential data only reaches approved private models

- Maintaining full audit logs of every AI agent action what went in, what model processed it, what came out, who accessed it

- Enforcing role-based access controls so analysts use AI tools within defined permissions

- Produce monthly privacy compliance reports for senior leadership

Coordinating with External Development Partners :

- Serving as Tristones technical point of contact for any outsourced developers or firms building AI modules

- Reviewing all code from external partners before deployment checking security, data handling, and quality

- Writing technical specifications that translate analyst workflow requirements into developer briefs

- Managing all code in a private GitHub repository with documentation Tristone always owns and controls the codebase

Continuous Improvement & Fine-Tuning :

- Monitoring AI agent outputs daily : track accuracy, hallucination rates, and analyst feedback then improve prompts and configurations

- Fine-tuning models on Tristone-specific financial language over time starting with prompt engineering, progressing to RAG, and eventually supervised fine-tuning

- Evaluating new AI tools monthly and recommend adoption where there is clear ROI

Training & Supporting the Analyst Team :

- Running onboarding sessions for analysts on how to use AI tools effectively practical, not theoretical

- Building a simple internal dashboard showing team AI usage and time saved per person

- Being the go-to person when an agent produces a wrong output diagnose it and fix it quickly

- Complying with IT policies and procedures

- Maintaining security of information at all times

Experience & Qualification :

- 2- 4 years of hands-on software development at least 1 year working specifically with LLMs, AI agents, or NLP systems

- At least one AI project currently in production (used by real users, not a demo) you must be able to demonstrate this

- Degree in Computer Science, Engineering, or Mathematics or demonstrable self-taught capability evidenced by public GitHub work

- Strong written and spoken English, you will write technical documentation, analyst guides, and developer briefs

Preferred :

- Experience in financial services, fintech, or investment research

- Previous experience as a solo technical lead someone who has owned a project end-to-end, not just contributed

- Familiarity with data privacy regulations relevant to financial services (GDPR, India DPDP Act 2023, SOC 2 principles)