About the Role
We are looking for an LLM Engineer who is ready to get their hands dirty immediately.
You will partner with our current high-performance team to ship product features fast.
The Role: Builder First, Architect Second
This is not an "ivory tower" architecture role. You must be ready to
contribute code from Day 1
. We need a leader who thrives in ambiguity, makes rapid decisions, and balances "perfect architecture" with the startup reality of "shipping today."
You will act as the engine of our engineering team—transforming broad business goals into working software with minimal friction.
Key Responsibilities
1. Immediate Contribution & Velocity
Ship Fast:
You will code core features of the AI platform immediately. We expect
deployments to happen daily, not monthly.
Rapid Prototyping:
Quickly build and iterate on Agentic workflows (using LangChain/LangGraph) to test product hypotheses. You know when to build an "MVP" and when to build "Enterprise Grade."
Bias for Action:
Eliminate analysis paralysis. You will make technical trade-offs quickly
to keep the team moving forward.
2. Python-Centric Engineering
Hands-On Coding:
serve as the primary contributor to our
Python
codebase. You will
write clean, asynchronous code (FastAPI, AsyncIO) that handles complex agent orchestration.
Production AI:
You won't just tweak prompts; you will build the serving infrastructure, vector retrieval pipelines (RAG), and evaluation loops that make our agents reliable in production.
3. Strategic Scalability
Evolving Architecture:
While you ship fast, you will ensure we don't code ourselves into a corner. You will design event-driven systems (NATS/Kafka) that allow us to scale 10x without a rewrite.
Owner Mindset:
You will treat the product as your own. This means caring about "Unit Economics" and "Cost of Delay" as much as code quality.
Requirements The "Startup DNA"
●
Readiness to Contribute:
You are comfortable jumping into an existing codebase and pushing commits within your first week.
Adaptability:
You thrive in an environment where priorities can shift.
Pragmatism:
You understand that "Done" is better than "Perfect." You focus on business value over over-engineering.
Technical Expertise
Python Mastery:
Expert-level Python skills are non-negotiable. You know the ecosystem (Pydantic, Poetry, FastAPI) inside and out.
AI Engineering:
Experience building actual products with LLMs (not just tutorials). You understand the challenges of context windows, latency, and hallucination.
Architecture background:
10+ years in engineering, with a track record of designing systems that survived rapid scaling. Experience with Microservices and Event-Driven Architecture.
Infrastructure:
Solid grasp of AWS and Kubernetes—you can fix a broken pipeline or deploy a container without waiting for a dedicated DevOps engineer.
What We Offer
High Impact:
No bureaucracy. Your code goes to production. Your decisions shape the company.
Growth:
A fast-track path to
be a key person on the product
.
Culture:
A team of senior experts who value "Delivery in 1 Second" and relentless improvement. We work hard, move fast, and measure results.