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PrecisionERP / PrecisionIT · Toronto, Ontario, Canada

Generative AI Engineer

mid_levelcontractPosted yesterday
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Stack mentioned

llmragagentic-ailangchainazureopenaimicroserviceskubernetesmlopssnowflakepythonobservabilitygenerative-aivector-databasesartificial-intelligencemachine-learningai-safety

Senior Generative AI Engineer / AI Engineer

PrecisionERP/IT is seeking a Senior Generative AI Engineer to design, build, and scale enterprise AI systems, Generative AI applications, and intelligent agents.

This is a 1-year contract position based in downtown Toronto. The role requires onsite presence at least 3 days per week.

Responsibilities

- Design, develop, and deploy production-grade AI and Generative AI solutions.

- Build enterprise GenAI applications using LLMs, RAG, embeddings, vector search, and AI agents.

- Design and implement Retrieval-Augmented Generation architectures for enterprise use cases.

- Develop AI agents using frameworks such as LangChain, Semantic Kernel, and Azure OpenAI.

- Fine-tune, optimize, and evaluate LLMs for business and enterprise applications.

- Build scalable APIs, microservices, and enterprise system integrations.

- Deploy AI/ML solutions on Azure cloud and Azure Kubernetes Service.

- Implement MLOps practices for model deployment, monitoring, and continuous improvement.

- Work with Snowflake and enterprise data platforms to support AI workloads.

Required Qualifications

- 6+ years of experience in AI, Generative AI, or Machine Learning engineering.

- Strong experience working in Azure cloud environments.

- Hands-on experience building end-to-end AI solutions in production.

- Experience building Generative AI applications using LLMs, RAG, and AI agents.

- Experience with Azure OpenAI, LangChain, Semantic Kernel, or similar AI frameworks.

- Experience with Snowflake or other enterprise data platforms.

- Strong Python programming skills.

- Experience building APIs and working with microservices architecture.

- Experience with Azure Kubernetes Service or similar container platforms.

- Experience with MLOps, model deployment, monitoring, and optimization.

Nice to Have

- Experience with Azure AI Search, Azure AI Foundry, Azure Machine Learning, or Microsoft Fabric.

- Experience with LLMOps, Responsible AI, guardrails, observability, and enterprise AI governance.

- Experience working in large enterprise or regulated environments.

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