Backend AI Engineer

Nexxa.ai; Canada; On-site; CAD 120,000 - 180,000; Full time

Job summary

Nexxa.ai is building the foundational AI systems for heavy industries, enabling machines, systems and operations to think, decide and act autonomously across manufacturing, infrastructure, logistics and legacy environments. We are seeking a Backend AI Engineer to design, build, and own the core AI infrastructure and services powering Nexxa's products in production.

This role blends backend software engineering with ML infrastructure and systems architecture to deliver scalable, reliable AI

Qualifications

• 4-8+ years of backend software/ML infra experience.
• Strong API and microservice design skills with TypeScript/Node.js.
• Hands-on production backend systems experience at scale.
• Experience integrating ML/Generative AI models into backend services.
• Knowledge of cloud infra and containerization.
• Experience with data pipelines and ML memory architectures.
• Familiarity with retrieval-augmented generation (RAG) systems.
• Understanding of system design, security, and observability.
• Bachelor's degree in CS or related field.

Responsibilities

• Design, build, and maintain backend services and APIs powering GenAI and CV model integrations.
• Build and own AI/ML infrastructure: model-serving, inference, data pipelines, embedding/vector stores.
• Architect scalable systems for real-time and batch AI workloads across industries.
• Implement RAG pipelines and orchestration layers linking models to data sources.
• Develop APIs and microservices connecting AI systems to customer data and legacy systems.
• Ensure reliability, performance, and observability of backend AI systems through CI/CD and testing.
• Collaborate with ML engineers, product, and customer teams to translate requirements into backend capabilities.
• Evaluate and integrate models into production pipelines; manage versioning and deployment.

Skills

Backend engineering

TypeScript/Node.js

Python (ML)

Distributed systems

ML model integration

Cloud infrastructure

Data pipelines

RAG systems

System design

Cross-functional collaboration

Education

Bachelor's degree in Computer Science or related field

Tools

Docker

Kubernetes

AWS

GCP

Azure

Kafka

gRPC/WebSockets

PyTorch/TensorFlow/OpenCV

Job description

Nexxa is building the best AI systems for heavy industries - enabling machines, systems and operations to think, decide and act autonomously across manufacturing, large-scale infrastructure, logistics and legacy environments.
Our mission is to translate deep technical breakthroughs into operational reality, solving some of the hardest systems-level problems in industry.

Role Overview

We're looking for Backend AI Engineers to design, build, and own the core AI infrastructure and services that power Nexxa's products in production. Where our Forward Deployed Engineers embed with customers to deliver solutions on the ground, this role builds the systems that make those solutions possible at scale: model-serving pipelines, inference and orchestration layers, data pipelines, and the APIs and microservices that connect Generative AI, Computer Vision, and Machine Learning models to real enterprise environments.

This role is a blend of backend software engineering, ML infrastructure, and systems architecture. You'll design distributed systems, integrate and serve models in production, and build the reusable platform capabilities that our customer-facing and product teams depend on.

Key Responsibilities

• Design, build, and maintain backend services and APIs that power GenAI, LLM, and Computer Vision model integrations across Nexxa's products.

• Build and own core AI/ML infrastructure: model-serving pipelines, inference services, data pipelines, and embedding/vector stores.

• Architect scalable, production-grade systems for real-time and batch AI workloads across manufacturing, infrastructure, and logistics domains.

• Implement and optimize RAG systems, prompt/context pipelines, and orchestration layers connecting models to enterprise and operational data sources.

• Build robust APIs, microservices, and integration layers connecting AI systems to customer data, legacy systems, and existing infrastructure.

• Own the reliability, performance, and observability of backend AI systems - logging, monitoring, testing, and CI/CD for ML services.

• Collaborate closely with Forward Deployed Engineers, ML engineers, and product teams to translate customer and field requirements into reusable, hardened backend capabilities.

• Evaluate and integrate ML/CV/LLM models into production backend systems; manage model versioning, rollout, and deployment pipelines.

• Produce clear technical documentation: architecture diagrams, API specs, and runbooks for internal and customer-facing teams.

• Mentor engineers and contribute to internal backend engineering best practices.

Qualifications

• 4-8+ years of experience in backend software engineering, ML/platform engineering, or similar roles.

• Strong proficiency in TypeScript/Node.js (our primary backend language), with strong API and microservice design skills. Working proficiency in Python is a plus for ML/model integration work.

• Hands-on experience building and operating production backend systems at scale - distributed systems, databases, message queues.

• Experience integrating ML or Generative AI models (LLMs, multimodal models) into backend services - inference, orchestration, and evaluation.

• Solid understanding of cloud infrastructure (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).

• Experience designing and operating data pipelines (batch and/or streaming) across structured and unstructured data.

• Hands-on experience building retrieval-augmented generation (RAG) systems and AI memory architectures - retrieval pipelines, vector stores, context management, and long-term/session memory for LLM applications.

• Strong grasp of system design fundamentals: scalability, reliability, security, and observability.

• Comfortable working cross-functionally with ML engineers, product, and customer-facing teams.

• Bachelor's degree (or higher) in Computer Science or a related field.

Preferred

• Familiarity with ML frameworks (PyTorch, TensorFlow, OpenCV) sufficient to integrate, serve, or evaluate models, even without training them yourself.

• Experience with MLOps tooling: model registries, feature stores, CI/CD for ML, and monitoring/observability for ML systems.

• Background in event-driven or real-time systems (Kafka, gRPC, WebSockets).

• Experience in industrial, IoT, or operational technology (OT) environments.

• Experience in startup or high-growth environments.

What We're Looking For

• A backend engineer who wants to build the infrastructure powering real-world autonomous AI systems.

• Someone who can architect for scale and reliability while still moving fast.

• A systems thinker who enjoys turning ambiguous AI capabilities into dependable, production-grade backend services.

• A strong collaborator who partners well with ML engineers, Forward Deployed teams, and product.

Why Join Nexxa.AI?

Innovative Environment: Build the foundational systems behind groundbreaking AI and automation technologies transforming heavy industries.

Collaborative Culture: Be part of a team that values innovation, discipline, and continuous improvement.

Professional Growth: Benefit from significant opportunities for career development and advancement.

Competitive Compensation: Enjoy a comprehensive salary and equity package reflective of your expertise and contributions.