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Slack Bot Developer/Teacher for Company Documentation

July 9, 2026

We're a growing service company looking for an experienced developer to build a Slack bot that answers employee questions about our HR policies, SOPs, and internal documentation. Team members will tag the bot in a channel, ask a question in plain language, and receive a conversational, accurate answer grounded in our documented materials.

**This is a build + teach engagement.** I have no coding background, and a core requirement of this project is that you walk me through your decisions and architecture as you build, so I can understand, maintain, and eventually extend the system myself. If you're a strong developer but don't enjoy explaining your work, this isn't the right fit.

## What You'll Build

A production-ready Slack bot with the following architecture:

- **Slack integration** using Slack's Bolt framework (Python or Node.js — your recommendation welcome)

- **Retrieval-Augmented Generation (RAG)** pipeline: questions are matched against our documentation via semantic search, and relevant context is passed to an LLM for a conversational answer

- **Vector database** (Pinecone, Weaviate, or a comparable option you can justify) storing embeddings of our policies, SOPs, and transcripts

- **OpenAI API** integration for embeddings and chat completions

- **Document ingestion pipeline** that can handle multiple source formats: Word docs, PDFs, spreadsheets, and plain-text transcripts (e.g., exported Loom video transcripts)

- **Source citations** in bot answers, so users can see which policy or document the answer came from

- Deployment to a cloud environment (AWS, Heroku, Railway, or similar) with clear instructions for how it runs and how to restart or update it

## Technical Requirements

You should have demonstrable experience with:

- Slack app development (Bolt framework, event subscriptions, OAuth/permissions setup)

- OpenAI's API (chat completions and embeddings)

- RAG architecture and vector databases (Pinecone, Weaviate, Qdrant, pgvector, or similar)

- Python or Node.js backend development

- Cloud deployment and basic DevOps (environment variables, API key security, uptime)

**In your proposal, please link to or describe at least one similar project you've built** — ideally a Slack bot, a RAG system, or an LLM-powered internal tool.

## Deliverables

1. A working Slack bot deployed to production and connected to our Slack workspace

2. Document ingestion process (with instructions or a simple tool for me to add new documents myself as our documentation grows)

3. Full source code in a repository I own, with clear comments

4. **Written documentation** covering: system architecture, how each component connects, how to add/update documents, how to update API keys, and common troubleshooting steps

5. **Teaching sessions**: recorded screen-share walkthroughs (or live calls) at each major milestone explaining what was built and why — I estimate 3–5 sessions of 30–60 minutes

6. A handoff session at the end where we test the bot together and review maintenance procedures

## Communication & Working Style

- Regular progress updates (at minimum, 2x per week)

- Willingness to explain decisions in plain English, not just technical jargon

- Patience with beginner questions — teaching is part of the paid scope, not a favor

- Fluent written and spoken English

- Availability for scheduled video calls (please note your time zone in your proposal)

## Scope Notes

- Initial document set is modest, but the system should be designed to scale as our documentation library grows significantly

- Future phases may include: automatic transcript ingestion from Loom, additional Slack channels/workflows, and analytics on what questions get asked — mention if you have experience with any of these

- I will provide: Slack workspace admin access, OpenAI API account, and all documentation to be ingested

## How to Apply

In your proposal, please include:

1. A brief description of a similar project you've built (links or screenshots appreciated)

2. Your recommended tech stack for this project and a one-paragraph explanation of why

3. Your approach to the teaching/documentation component

4. Estimated timeline and total cost (fixed price preferred; open to milestone-based payment)

5. Your time zone and general availability

Proposals that are clearly personalized and address the teaching component will be prioritized. Generic copy-paste proposals will be declined.

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