Sahibjot Singh Bhoday

LLM & Prompt Engineering Experience:
I have been working with LLM’s for over 3 years now, and in 2025 I first applied my experience to solve a real business problem, at SmartSequence (a team of 2 core members and we hire appointment setters) I designed/developed/tested and delivered 6 tailored AI systems that are fully end-to-end and save all the firms over $45,000 USD a year minimum. I’ve built systems using OpenAI, Perplexity, LLaMA 3, and Mistral models, fine-tuning them with tailored constraints and strict protocols to ensure accuracy is met for the intended task.

I have my own startup as well, Quanta Co. (2 core members), where we help portfolio managers stay informed about current portfolio holdings through an AI alert system & tailored quantitative analysis. There are over 10 AIs that work together to formulate an output that is sent to the user. Each AI/ AI system has been thoroughly tested and tuned by me to ensure a ~0 error environment, even when an AI is responsible for everything the client will see and act on.

For all 8 deliveries of my AI systems, n8n & langchain/graph were used to develop my AI infrastructure.

I have countless experience using all types of local and cloud-based LLMs in personal, academic, and professional scenarios.
What My LLM & Prompt Engineering Work Delivers (On-Premises and Cloud-Hosted):

SmartSequence (CTO/Co-founder)

LinkedIn Outreach Agent(For Commercial Real Estate/Private Equity Firms): Scrapes LinkedIn likers & commenters from user input. OpenAI AI reads through every lead and does a weighted average score of how well leads career and culture fit the criteria of the firm’s ICP. A chain of Local LLMs that clean data, then the Icebreaker generator AI reads all cleaned information and writes a message that follows a structure it has been trained on and will match the CEO’s speech model(achieved through iterative prompt engineering to have a consistent and accurate tone while allocating for heavy personalization). LinkedIn connections are sent out and on acceptance, my icebreaker is sent to the lead and if the lead is convinced by my message, then they schedule a call via Calendly and have a meeting with the CEO, and the CEO can then close the deal and secure funding for the next commercial property investment. This project has been delivered 6 times with alternating techstacks & models that allocate for client needs.

QuantaCo. (Founder)

AI Investment Analyst (For Portfolio Managers): A pipeline that ingests market data with TwelveData API & Perplexity Sonar for financial news every 15 mins. Quantitative models in C++ & ML Python libraries run for market data, and an AI cleans up the recent Sonar ingested. I would write mroe but hit word limit

I am applying for a senior role at the firm not one that pays $3000, I bring real value.