Backend AI Engineer — Scalable ML Infra

Nexxa.AI; Sunnyvale (CA); Hybrid; USD 150,000 - 210,000; Full time

Job summary

Nexxa.AI is seeking a Backend AI Engineer to design, build, and own core AI infrastructure that powers Nexxa’s products in production. You will develop model-serving pipelines, inference services, and data pipelines, connecting Generative AI, CV, and ML models to enterprise environments.

This role blends backend software engineering, ML infrastructure, and systems architecture, requiring you to craft scalable, reliable systems and collaborate with cross-functional teams.

Qualifications

• 4–8+ years in backend software engineering or ML infrastructure.
• Strong API and microservice design; production experience.
• Experience integrating ML/AI models into backend services.

Responsibilities

• Design, build, and maintain backend services and APIs powering GenAI, LLM, and Computer Vision integrations.
• Build and own AI/ML infra: model-serving pipelines, inference services, data pipelines, embedding/vector stores.
• Architect scalable, production-grade systems for real-time and batch workloads.
• Implement RAG systems, prompt pipelines, and orchestration layers.
• Create robust APIs and integration layers with enterprise data and legacy systems.
• Ensure reliability, observability, and CI/CD for ML services.
• Collaborate with Forward Deployed Engineers, ML engineers, and product teams.
• Manage model versioning, rollout, and deployment pipelines.
• Document architecture and API specs; produce runbooks.

Skills

Backend engineering

TypeScript/Node.js

Python

Distributed systems

Cloud platforms (AWS/GCP/Azure)

Docker & Kubernetes

ML model integration

RAG systems

APIs / microservices

Education

Bachelor’s degree in Computer Science or related field

Tools

Kafka

TensorFlow

PyTorch

OpenCV

gRPC

WebSockets

Job description

Nexxa.AI is seeking a Backend AI Engineer to design, build, and own core AI infrastructure that powers Nexxa’s products in production. You will develop model-serving pipelines, inference services, and data pipelines, connecting Generative AI, CV, and ML models to enterprise environments.

This role blends backend software engineering, ML infrastructure, and systems architecture, requiring you to craft scalable, reliable systems and collaborate with cross-functional teams.