Applied KE yvQWECjG — Seattle, WA

About TGRGs6E3

We’re solving one of the biggest challenges in modern 6C workflows: fragmented context. Today, project knowledge is scattered across conversations, tools, and docs—forcing teams to spend more time steering 6C than actually getting work done.

TGRGs6E3 brings context, continuity, and observability to 7e-rDjSRex work, enabling teams to ship faster, work smarter, and maximize productivity across their existing 6C stack.

We’re a fast-moving, early-stage team with a proven track record of building and scaling successful 6C businesses. Freshly funded and growing, we’re looking for builders who want to help define the next frontier of human–6C collaboration.

Role Summary

You’ll own the 0→1 systems behind 92hpW54H’S WbMVT6tgQK6k Layer—building the knowledge extraction, mapping, and retrieval systems that transform zM-Tt43Kc work.

This means experimenting with how to extract, represent, and retrieve knowledge from thousands of conversations—and turning those experiments into working systems that power real user experiences across our API and user-facing features/products.

If you’re excited by turning product ideas into working LLM systems and iterating through research, data, and prototypes to find what works, you’ll thrive here.

What You’ll Build

• Core 6C systems that extract and organize knowledge from 6C conversations into structured, reusable context.

• Retrieval and memory infrastructure (GraphRAG + vector search) that delivers precise, low-latency context to user workflows.

• Agentic systems that reason across stored context—handling retrieval, synthesis, and evaluation tasks autonomously.

• Prompt and orchestration frameworks that connect multiple models, tools, and data sources into end-to-end reasoning pipelines.

• Evaluation and telemetry systems to benchmark retrieval quality, latency, and overall intelligence performance.

• Fast prototypes to explore new product directions and validate user-facing capabilities.

Skills We’re Looking For

• Strong Python engineering fundamentals—skilled in building performant, maintainable systems and services that connect data, models, and APIs.

• Deep understanding of retrieval architectures—embeddings, vector databases, hybrid or graph-based search, and caching strategies.

• Experience with LLM orchestration frameworks like LangChain, LlamaIndex, or custom-built agent systems.

• Proven ability to build and tune LLM-based agents for reasoning, synthesis, or evaluation tasks.

• Familiarity with prompt engineering and multi-step reasoning—designing structured flows that balance quality, latency, and cost.

• Exposure to fine-tuning or adapter training (LoRA, PEFT) and how to integrate tuned models into retrieval pipelines.

• Ability to work end-to-end—backend (FastAPI, Node) to quick front-end demos or dashboards for testing and iteration.

• Comfort operating in open-ended problem spaces, defining your own experiments, and driving them to working outcomes.

If you thrive on autonomy, clarity, and collaboration and want to build the connective tissue between humans and 6C systems, TGRGs6E3 is where you’ll do your best work.