AI Engineer (Agentic Systems)
- Canada
Full-time
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Job details
- Job type
- Full-time
- Posting language
- English
- Posted
Original job description
Overall – 8+ | AI Exp – 3+
- Python (primary for AI pipelines, LangChain, asynchronous processing).
- C# / .NET (common across Pearson VUE microservice integrations and Assist Portal backends).
- Azure OpenAI Service, Azure Cognitive Search / AI Search, Azure Container Apps / Azure Kubernetes Service (AKS), Azure App Services.
- Deep understanding of the 2-phase RAG pipeline: document ingestion, chunking strategies, vector embedding generation, similarity retrieval, and context-bounded prompt construction.
- Experience calculating and tuning vector similarity metrics (e.g., Cosine Similarity thresholds) to filter irrelevant queries before hitting LLMs.
- Hands-on proficiency with LangChain, LangGraph, LlamaIndex, or Semantic Kernel.
- Managing multi-workspace prompt templates, system instructions, and dynamic few-shot prompt injection.
- Experience with Azure OpenAI Service (GPT-4o, GPT-4, text-embedding models) and open-source models (Llama, Falcon, Mistral) or multi-model routing (Gemini / Claude).
- Optimizing token usage, latency, temperature/top_p parameters, and fallback/circuit-breaker logic.
- Building performant, asynchronous REST APIs for embedding generation, batch document indexing, chat streaming (SSE/WebSockets), and workspace administration.
Parsing, cleaning, and tokenizing multi-format inputs (PDFs, Word docs, HTML Self-Help Articles, URLs).
More about this job
Responsibilities
Build and optimize agentic AI systems, including two-phase RAG pipelines for document ingestion, retrieval, and context-bounded prompt construction. Develop asynchronous APIs and integrations for embedding generation, document indexing, chat streaming, and workspace administration.
Requirements
Requires 8+ years of overall experience and 3+ years of AI experience, with Python as the primary language and C#/.NET experience for integrations. Candidates should have hands-on experience with Azure AI services, RAG, vector similarity tuning, AI orchestration frameworks, prompt management, model optimization, and processing documents in multiple formats.
Skills
- Python
- C#/.NET
- Azure OpenAI Service
- Azure AI Search
- Azure Container Apps
- Azure Kubernetes Service
- Azure App Services
- Retrieval-Augmented Generation
- Vector Embeddings
- LangChain
- LangGraph
- LlamaIndex
- Semantic Kernel
- Prompt Engineering
- Asynchronous REST APIs
- Document Processing
Visa sponsorship
Not detected in the job text
Categories
- Technology
- Software
- Engineering
Keywords
- Python
- C#/.NET
- Azure OpenAI Service
- Azure Cognitive Search
- Azure AI Search
- Azure Container Apps
- Azure Kubernetes Service
- Azure App Services
- Retrieval-Augmented Generation
- Document Ingestion
- Chunking Strategies
- Vector Embeddings
- Cosine Similarity
- LangChain
- LangGraph
- LlamaIndex
- Semantic Kernel
- Prompt Templates
- Few-Shot Prompting
- GPT-4o
- GPT-4
- Llama
- Falcon
- Mistral
- Gemini
- Claude
- Asynchronous REST APIs
- Server-Sent Events
- WebSockets
- Document Processing