Machine Learning Engineer designing and operating AI platform components for Mozilla. Collaborating with teams to ensure efficient and reliable deployment of machine learning models.
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Senior AI Application Engineer
Posted via LinkedIn Recruiter (not a company profile)
Posted yesterday
About the role
- Senior AI Application Engineer needed for hybrid role in Woodbridge, ON. Design and build AI-powered applications with LLMs, multi-agent systems, and full stack development.
Responsibilities
- Design, build, and maintain end-to-end AI-powered applications across frontend, backend, and AI/LLM integrations, including multi-agent orchestration patterns. Develop user-facing solutions such as copilots, conversational interfaces, intelligent search, and workflow automation. Build AI-powered integrations for enterprise SaaS platforms including Salesforce, Workday, and ServiceNow. Design guardrails, output validation, monitoring, and fallback mechanisms for AI behavior. Develop evaluation frameworks and testing strategies using automated and human-in-the-loop validation. Collaborate with Data Engineering, Machine Learning, Security, Architecture, QA, and Operations teams. Participate in architecture reviews, security assessments, and threat modeling. Contribute to AI engineering standards, reusable frameworks, governance practices, and development patterns.
Requirements
- 5+ years of experience building modern full stack applications. Strong development experience with Java and/or Node.js and working knowledge of Python. Experience with React, Next.js, REST APIs, and modern web application development. Hands-on experience integrating LLMs and AI/ML services into production applications. Expertise in prompt engineering, Retrieval Augmented Generation (RAG), agent orchestration, and tool integration. Experience designing and managing non-deterministic systems, including validation frameworks, confidence scoring, and graceful degradation strategies. Knowledge of AI security practices including OWASP principles, threat modeling, prompt injection mitigation, and data protection. Experience implementing AI observability, monitoring, logging, drift detection, and performance tracking. Experience integrating enterprise platforms such as Salesforce, Workday, and ServiceNow. Cloud-native development experience with AWS, OpenShift/Kubernetes, CI/CD pipelines, and HashiCorp Vault. Experience building or integrating agent frameworks and evaluation harnesses. Strong understanding of software engineering best practices, SDLC governance, and enterprise delivery standards. Bachelor’s degree in Computer Science, Software Engineering, Artificial Intelligence, or a related discipline.
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