Founding Backend Engineer; AI Focus - Atrix

At Atrix, our journey began with a simple belief:
Breakthrough medicines and technologies change lives, and the people making them deserve better tools.

We often celebrate the final moment: a patient receiving a life-saving therapy or a groundbreaking treatment becoming standard of care.
But behind that moment is a complex, coordinated effort that begins years earlier.

Pharmaceutical and med device companies shoulder this responsibility every day:

• Advancing science from lab to clinic

• Navigating regulatory and access barriers

• Ensuring safe, evidence-based adoption in the real world

They’re not just bringing products to market; they’re shaping the future of care.

Yet these organizations are often held back by outdated workflows and siloed data, unable to fully harness the knowledge that already exists across their teams.

Atrix was built to change that.

We exist to support the mission of those who dedicate their lives to creating and delivering innovations that impact global health.

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.

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 (Postgre
  
  SQL) and ORMs (SQL Alchemy 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, Lang Chain, Llama Index, or other LLM orchestration tools

• Exposure to RAG or context injection workflows

• Experience with AWS, Terraform, Kafka, or Py Torch

• Background in healthcare, data security, or regulated environments

Mi…