Location: [Kanpur / Hybrid / Remote]
Type: Part-time
Reports to: Founder / Managing Partner
Collaboration: Works closely with advisory, research, and product teams
About Suprabhaatam Partners
Suprabhaatam Partners is a boutique advisory firm offering premium investment banking, transaction diligence, and strategic advisory services, supported by proprietary research and thought leadership. We are now building an in-house AI capability centered on large language models (LLMs) to automate and enhance core workflows in M&A, diligence, and strategy.
Role Overview
As a Technical Associate – Large Language Models, you will design, develop, and deploy LLM-based solutions tailored to our investment banking and advisory workflows. You will translate domain processes (e.g., deal screening, diligence checklists, report drafting, market mapping) into AI-automatable tasks and build the models, pipelines, and integrations needed to productionize these solutions.
This is a part-time role suited for someone with deep expertise in LLMs and a strong interest in applying AI to real-world financial and strategic problems. Both freshers with exceptional LLM skills and experienced practitioners are welcome.
Key Responsibilities
LLM Design & Development
- Design and implement LLM-based solutions for:
- Automated document review and summarization (CIMs, diligence reports, contracts).
- Deal and company screening based on textual and structured data.
- Drafting sections of reports, memos, and client materials.
- Q&A systems over internal knowledge bases and past transactions.
- Fine-tune and adapt pre-trained models (e.g., open-source LLMs) to our domain and use cases.
- Implement retrieval-augmented generation (RAG) pipelines using internal documents and data.
- Evaluate model performance, accuracy, hallucination rates, and safety.
Data & Pipeline Engineering
- Build data ingestion and pre-processing pipelines for documents, databases, and APIs.
- Design labelling and annotation strategies for supervised fine-tuning and evaluation.
- Ensure data quality, security, and access controls for sensitive client and transaction data.
- Implement versioning and reproducibility for models and datasets.
Integration & Automation
- Integrate LLMs with internal tools (e.g., document management, CRM, research platforms).
- Develop APIs, microservices, or plugins to embed AI capabilities into existing workflows.
- Automate repetitive tasks (e.g., initial drafts, data extraction, standard analyses) to improve productivity.
- Monitor model performance in production and iterate based on feedback.
Collaboration with Domain Teams
- Work closely with advisors and analysts to understand workflows and pain points.
- Translate business requirements into technical specifications and solution designs.
- Train and support non-technical users on how to effectively use AI tools.
- Continuously gather feedback to refine models and features.
Governance, Security & Best Practices
- Implement safeguards against data leakage, prompt injection, and misuse.
- Follow best practices for model governance, documentation, and auditability.
- Stay updated on the latest LLM research, tools, and frameworks relevant to our use cases.
What You’ll Bring
Essential
- Expert knowledge of large language models, including architectures, training, and fine-tuning.
- Hands-on experience with Python and ML frameworks (e.g., PyTorch, Transformers, LangChain, LlamaIndex).
- Clear understanding of how to productionize models: APIs, deployment, monitoring, and scaling.
- Experience with RAG, vector databases, embeddings, and related techniques.
- Ability to work with unstructured text data (documents, reports, emails) and structured data.
- Fresher or experienced; depth in LLMs and solution-building is critical.
Preferred
- Prior work applying LLMs to finance, legal, consulting, or knowledge-intensive domains.
- Familiarity with cloud platforms (AWS, GCP, Azure) and containerization (Docker, Kubernetes).
- Experience with evaluation frameworks, prompt engineering, and safety mitigations.
- Interest in investment banking, M&A, or strategic advisory concepts.
What Success Looks Like (First 6–12 Months)
- Delivers at least 2–3 production-grade LLM solutions that materially improve team productivity.
- Establishes robust data and model pipelines that are secure, maintainable, and scalable.
- Becomes the go-to person for AI/LLM strategy and implementation within the firm.
- Enables advisors and analysts to routinely use AI tools in their daily workflows.
- Contributes to a clear roadmap for expanding AI capabilities across services and products.
What We Offer
- Opportunity to build an in-house AI function from the ground up.
- Direct exposure to real-world IB, diligence, and strategy problems.
- Flexible, part-time engagement with scope for increased responsibility.
- Close collaboration with leadership and domain experts.
- Freedom to choose tools and architectures, with a focus on impact and practicality.
How to Apply
Option 1: Click on 'Apply Now' to fill the required information along with attaching your latest CV and the cover letter having a brief note (300–500 words) on why you are interested in this role, and links to relevant work (GitHub, projects, papers, demos). If possible, include a short description of one LLM project you’ve built, the problem it solved, and your specific contributions.
Option 2: Send your CV, a brief note (300–500 words) on why you are interested in this role, and links to relevant work (GitHub, projects, papers, demos) to:
Email: careers@suprabhaatampartners.com
Subject: Application – Technical Associate (LLM)
