岗位大厅/Engineering/Founding Backend Engineer (AI Focus) - Atrix

Pear Vc · 35天前 · 来源 ATS 官方

Founding Backend Engineer (AI Focus) - Atrix

New York City办公方式未标注
全职Engineering
薪资未披露

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必备技能

AIAPIAWSAgentic AIData PipelinesDistributed SystemsDjangoEmbeddingsFastAPIFlask

免费注册后解锁"你的匹配分 vs 高分画像"与个人技能缺口。

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职位描述

[https://app.ashbyhq.com/api/images/user-content/cca476c0-947e-4006-a2cb-409350de667a/7f607394-a435-4f65-a46a-ad290a1fa43b/Screenshot%202025-02-14%20at%2010.18.39%E2%80%AFAM.png]

Breakthrough medicines all start the same way: years of research, mountains of data, and countless decisions made by medical teams within the world's premier biopharma labs.

These decisions then determine which treatments make it to market, how doctors learn about them, and ultimately which patients get access to life-saving care and when.
We're at an inflection point. AI-powered drug discovery, precision medicine, and an explosion of real-world evidence have accelerated what's possible, but the teams translating science into patient access are drowning in data they can't use.

The tools haven't kept up with the stakes.
Atrix builds purpose-built AI for life sciences, designed for the accuracy and rigor biopharma requires.

We're live with top-10 pharmaceutical companies, scaling fast, and focused on one thing: helping the right treatments reach the right patients, sooner

THE ROLE DESCRIPTION

You’ll be a core builder of Atrix’s backend infrastructure, powering AI-native workflows that ingest unstructured data, structure it with AI, and deliver insights that matter—instantly and reliably.

You’ll work on scalable data pipelines, robust APIs, and real-time inference systems, supporting everything from complex agent workflows to customer-facing dashboards. Whether it’s building retrieval pipelines, optimizing async background workers, or designing clean, secure APIs, your work will be foundational to how our platform works and scales.

We're building a modular, agentic platform that connects to customer-approved data sources, transforms unstructured data using LLM-based agents, and delivers decision-ready intelligence to regulated teams.

You’ll tackle rich backend engineering challenges like:

- ⚙️ System Design & Reliability – Scale to handle massive amounts of records with fast response times

- 🧠 LLM Ops – Make AI outputs explainable, auditable, and efficient

- 🛠 Multi-Tenant Infra – Isolate customer data across parallelized pipelines

- 🚀 AI Performance Tuning – Optimize inference cost, caching, and latency

- 📡 RAG Pipelines & Contextual Workflows – Connect structured + unstructured data for real-world usage

You’ll work closely with the Engineering Lead and CEO, and collaborate across product, AI, and GTM. As one of our earliest backend engineers, you’ll influence everything from our architecture to hiring bar.

💡 This is an in-person role based in NYC, with flexibility for remote work on some days as needed.

RESPONSIBILITIES

This role is perfect for someone who thrives on solving deep technical problems, loves optimizing systems for speed and scale, and gets energized by seeing their work used in real-world, high-stakes environments. If you’re excited about powering AI workflows behind the scenes—and building infrastructure that’s as elegant as it is reliable—we’d love to talk.

In this role, you will:

- Design and own major modules of our backend architecture (APIs, workers, orchestration)

- Optimize performance and reliability of data processing and AI inference systems

- Build and maintain LLM-powered backend features and multi-step workflows

- Collaborate with product and AI teams to launch performant, production-grade AI features

- Improve observability, traceability, and modularity of backend systems

- Lead customer-focused feature delivery with high attention to security and compliance

Must haves

- 5+ years backend engineering experience in fast-paced product teams

- 2+ years of Python experience, including async programming

- Expertise with one or more frameworks: FastAPI, Flask, Django

- Strong experience with SQL (PostgreSQL) and ORMs (SQLAlchemy or equivalent)

- Experience building APIs, background workers, and distributed systems

- Understanding of how LLMs, embeddings, or RAG workflows function

- Startup experience or demonstrated ownership in complex backend projects

Nice to haves

- Familiarity with Celery, LangChain, LlamaIndex, or other LLM orchestration tools

- Exposure to RAG or context injection workflows

- Experience with AWS, Terraform, Kafka, or PyTorch

- Background in healthcare, data security, or regulated environments

WHY JOIN ATRIX AS A BACKEND ENGINEER?

🚀 Mission-Driven Impact
Your code will help life sciences teams deliver better treatments—faster. Every system you build supports real-world clinical outcomes.

💥 Real AI, Real Stakes
This isn’t research tooling. You’ll make AI work for real customers—ensuring reliability, explainability, and speed in high-stakes environments.

🧱 Deep Backend Ownership
Shape architecture, modular services, and engineering culture from day one.

📊 Scale + Complexity
You’ll design systems that operate on thousands of records, across multi-client, multi-agent environments—with LLMs at the core.

🌱 Early Team, High Growth
Be part of a tight-knit, mission-oriented team, and grow into our Backend Lead Engineer as we scale.

WHAT WE OFFER

- 💵 Compensation: Competitive salary + equity package

- 💪 Health & wellness support – Stipend + medical (vision, dental, health) insurance coverage

- 🌴 Unlimited PTO – Recharge when you need to

- 🧠 High learning velocity – Get exposed to AI, infra, GTM, and real customers daily

🈯 翻译这份 JD · 红灯 0 / 黄灯 2 / 绿灯 1点开 ▾
可以投——没有红灯,黄灯问题放进面试清单问清即可。
fast-paced → 流程不成熟、需求常变要问的问题:「节奏快」的交付周期是多久?需求由谁定?
competitive salary → 形容词,不是数字要问的问题:这个岗位的预算范围是多少?
nice to have → 加分项,不是门槛
词典只标"常见信号",不对公司下结论——红灯 = 面试里该当面确认的问题。想自己翻别的 JD:JD 翻译器 →
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公司 · Company

Pear Vc

Pear VC portfolio

New York City来源:ATS 官方

⚑ 岗位信息收录自公开招聘页(ATS 官方),以雇主官网为准