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 energetic 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).

📌 AI Engineer (Agentic Systems) (Canada)
🏢 HCLTech
📍 Canada