Senior AI Engineer

NovoEd, Inc.; California; Hybrid; USD 150,000 - 210,000; Full time

Benefits offered by this job

Benefits Package with time off

Holiday pay

Job summary

NovoEd, Inc. is a fast-growing product company applying cutting-edge AI capabilities to its core platform. Our Python backend stack includes FastAPI, Gunicorn, and Nginx with Celery for heavy background processing.

We seek a senior AI Engineer who blends backend engineering with applied AI to deliver fast, reliable, and scalable systems. You will design and deploy AI-powered backends, integrate LLMs and traditional ML models, optimize vector stores for RAG, and write clean Python code while

Qualifications

• 3–5+ years backend engineering experience in Python with FastAPI or Flask.

Responsibilities

• Design, develop, and deploy production‑grade AI‑powered backend systems.
• Integrate LLMs and ML models into scalable architectures.
• Optimize vector databases for retrieval‑augmented generation pipelines.
• Write clean, testable Python code following best practices.
• Focus on performance to minimize latency in AI workflows.
• Collaborate with product, backend, and frontend engineers to deliver cohesive solutions.

Skills

Python

FastAPI

Background processing

LLM integration

Celery

Performance tuning

AI deployment

Education

Masters Degree in related field

Tools

Docker

Kubernetes

CI/CD

Nginx

Job description

We’re a fast-growing product company integrating cutting-edge AI capabilities into our core offering to stay competitive and deliver exceptional value to customers. Our AI work spans task‑specific ML models, large language model (LLM) integration, and agentic systems that orchestrate multiple tools to produce end‑user results.

We run a Python-based backend (FastAPI + Gunicorn + Nginx) with heavy background job processing using Celery. We’re looking for a senior‑level AI Engineer who is equally strong in backend engineering and applied AI — capable of building production‑grade systems that are fast, reliable, and maintainable.

What You’ll Do

• Design, develop, and deploy production‑grade AI‑powered backend systems.
• Integrate LLMs and traditional ML models into performant, scalable architectures.
• Integrate and optimize vector databases for retrieval‑augmented generation (RAG) pipelines and other traditional ML queries.
• Write clean, well‑structured, and testable Python code following best practices.
• Capable of thinking about performance and ensuring optimal decision making to reduce latency.
• Build hybrid architectures that balance LLM calls with traditional ML.
• Debug complex, cross‑layer issues spanning backend, AI inference, and UI integration.
• Conduct thorough dev testing before QA handoff to ensure production reliability.
• Collaborate with product, backend, and frontend engineers to deliver cohesive solutions.

Must-Have Skills & Experience

• 3–5+ years professional backend engineering experience in Python, FastAPI or Flask, and background processing.
• Masters Degree in related field
• Proven record of deploying Python applications to production (not just scripts or academic work).
• Strong grasp of software design patterns
• Strong understanding of backend performance, parallel processing in background jobs and multi‑threading
• Proficiency in performance tuning specially for heavy AI models
• Applied machine learning experience — training, evaluating, and maintaining small task‑specific models.
• Familiarity with LLM integration, prompt engineering, and context window optimization.
• Proven ability to debug AI behavior, identify root causes, and make targeted fixes.
• Strong testing discipline for both backend and AI components.
• Experience with background processing with Celery or other major libraries
• Experience with monitoring APIs and background processing
• Experience with ensuring visibility and error reporting.
• Nice to have: experience with Docker, understanding of CI/D, deployment automation and Kubernetes

Who Will Succeed in This Role

• Independent problem solver — you can debug without constant supervision.
• Production mindset — you understand that reliability, scalability, and maintainability matter as much as accuracy.
• System thinker — you see backend, AI, and UI as a connected whole.

Why Join Us

• Direct impact on the company’s competitive edge.
• Small, fast‑moving team with high autonomy.
• Work on practical, real‑world AI applications — not just research.
• Opportunity to shape our AI architecture and best practices from the ground up.
• Benefits Package, with time off and Holiday pay

If you’re a backend‑first AI engineer who thrives in shipping production‑ready systems and knows how to make AI practical, fast, and reliable — we’d love to talk.