Nomad is building the financial operating system for fleets: fuel cards, real-time transaction processing, invoicing, and working-capital finance, increasingly automated by production AI. We are a small, fast-moving team that cares deeply about doing right by our customers, which in our business means getting the numbers exactly right, every time.

About You

You are a passionate and resourceful Senior Full Stack Engineer with strong experience building scalable, secure applications across the front-end and back-end. You are experienced with React, TypeScript, Node.js, and cloud technologies, and have hands‑on experience applying LLMs, machine learning, or data science to real-world products.

You enjoy working in a quick-paced environment, taking ownership of features from design through production, and solving complex technical problems. You care about code quality, security, reliability, and building AI-powered experiences that are practical and production-ready.

Key Responsibilities

Full Stack Engineering

- Design, develop, and maintain secure and scalable applications using Node.js, TypeScript, and React.
- Build and maintain REST APIs, backend services, and user-facing applications.
- Architect and implement cloud solutions using Google Cloud Platform (GCP).
- Own features end-to-end, from technical design and development through testing, deployment, and production support.
- Review code, troubleshoot production issues, and provide technical guidance to team members.

AI, LLM & Data

- Build and integrate AI/ML-powered features into Nomad's products and workflows.
- Develop applications using Large Language Models (LLMs) such as OpenAI, Gemini, Claude, or similar platforms.




- Work with technologies and approaches such as RAG, embeddings, vector search, AI agents, prompt engineering, and LLM APIs.
- Apply machine learning and data science concepts to solve product and business problems.
- Work with structured and unstructured data and support data-driven product development.
- Evaluate and improve the accuracy, reliability, performance, and cost of AI-powered applications.
- Implement security best practices across the application and AI/ML stack.
- Manage authentication, authorization, secrets, and customer data securely.
- Manage CI/CD pipelines and follow established code review and change management practices.
- Implement logging, monitoring, alerting, and production support processes.
- Maintain technical documentation and support SOC 2 and other compliance requirements.

Required Qualifications & Skills

Full Stack

- 5–7+ years of professional software engineering experience building and supporting production applications.
- Experience designing and developing REST APIs and backend services.
- Strong understanding of modern software architecture, testing, and development practices.
- Experience with Google Cloud Platform (GCP) or a comparable cloud environment.
- Experience with Git, CI/CD, code reviews, and production deployments.





AI / ML / Data

- Hands‑on experience building or integrating AI/ML capabilities into production applications.
- Practical experience with LLMs and Generative AI.
- Experience with one or more of RAG, embeddings, vector databases, AI agents, prompt engineering, or LLM APIs.
- Experience with Python for AI/ML, data processing, analytics, or backend development.
- Strong understanding of machine learning and/or data science concepts and their practical application.
- Experience working with structured and/or unstructured data.
- Ability to integrate AI/ML capabilities into full-stack applications.

Security & Cloud

- Strong understanding of web application and API security, including OAuth 2.0, JWT, CORS, and common application vulnerabilities.
- Experience with cloud infrastructure, monitoring, logging, and deployment.
- Familiarity with secure SDLC and production security practices.

Preferred Qualifications

- Experience with LangChain, LangGraph, LlamaIndex, or similar AI frameworks.
- Experience with Pinecone, pgvector, Weaviate, Vertex AI Vector Search, or similar vector databases.
- Experience with scikit-learn, TensorFlow, PyTorch, or similar ML frameworks.
- Experience with Google Vertex AI, Azure OpenAI, AWS Bedrock, or similar AI platforms.
- Experience building AI agents or agentic workflows.
- Experience with Docker, Kubernetes, Terraform, or microservices.
- Experience in SaaS, fintech, financial services, payments, transportation, or other data-intensive environments.
- Experience supporting SOC 2, ISO 27001, or similar compliance frameworks

📌 Senior Full Stack Engineer – AI/ML (Toronto)
🏢 NOMAD
📍 Toronto