GenAI Developer
3 hours ago
Winnipeg, Manitoba, Canada
Quantum World Technologies Inc.
Full-time
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We are seeking an experienced
Generative AI Developer (GenAI Developer)
with 8+ years of experience in software development, AI/ML engineering, and enterprise application development. The ideal candidate will have strong hands‑on experience building and deploying Generative AI solutions using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), prompt engineering, and AI-powered applications.
The candidate will collaborate with business stakeholders, data scientists, architects, and engineering teams to design, develop, integrate, and deploy scalable GenAI solutions that address complex business requirements.
Required Skills and Qualifications
8+ years of overall experience in software development, AI/ML engineering, or related technical roles.
Strong hands‑on experience with
Generative AI, Large Language Models (LLMs), and prompt engineering .
Strong programming experience in
Python .
Practical experience developing RAG-based applications and LLM-powered solutions.
Experience with vector databases such as Pinecone, Azure AI Search, Weaviate, Chroma, or FAISS.
Experience with LangChain, LangGraph, LlamaIndex, or similar AI development frameworks.
Knowledge of embeddings, semantic search, chunking strategies, and document processing.
Experience building REST APIs and integrating AI models with enterprise systems.
Hands‑on experience with cloud-based AI services, preferably Azure OpenAI or AWS Bedrock.
Understanding of machine learning fundamentals, NLP, and transformer architectures.
Experience with Git, CI/CD pipelines, Docker, and application deployment.
Strong analytical, problem‑solving, communication, and collaboration skills.
Preferred Qualifications
Experience with agentic AI, AI agents, and tool/function calling.
Knowledge of multi-agent orchestration and workflow automation.
Experience with Microsoft Azure AI Foundry or equivalent AI platforms.
Familiarity with LLM evaluation frameworks, observability, and model monitoring.
Experience with enterprise‑grade AI security, governance, and responsible AI practices.
Experience working in Agile/Scrum environments.
Generative AI Developer (GenAI Developer)
with 8+ years of experience in software development, AI/ML engineering, and enterprise application development. The ideal candidate will have strong hands‑on experience building and deploying Generative AI solutions using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), prompt engineering, and AI-powered applications.
The candidate will collaborate with business stakeholders, data scientists, architects, and engineering teams to design, develop, integrate, and deploy scalable GenAI solutions that address complex business requirements.
Required Skills and Qualifications
8+ years of overall experience in software development, AI/ML engineering, or related technical roles.
Strong hands‑on experience with
Generative AI, Large Language Models (LLMs), and prompt engineering .
Strong programming experience in
Python .
Practical experience developing RAG-based applications and LLM-powered solutions.
Experience with vector databases such as Pinecone, Azure AI Search, Weaviate, Chroma, or FAISS.
Experience with LangChain, LangGraph, LlamaIndex, or similar AI development frameworks.
Knowledge of embeddings, semantic search, chunking strategies, and document processing.
Experience building REST APIs and integrating AI models with enterprise systems.
Hands‑on experience with cloud-based AI services, preferably Azure OpenAI or AWS Bedrock.
Understanding of machine learning fundamentals, NLP, and transformer architectures.
Experience with Git, CI/CD pipelines, Docker, and application deployment.
Strong analytical, problem‑solving, communication, and collaboration skills.
Preferred Qualifications
Experience with agentic AI, AI agents, and tool/function calling.
Knowledge of multi-agent orchestration and workflow automation.
Experience with Microsoft Azure AI Foundry or equivalent AI platforms.
Familiarity with LLM evaluation frameworks, observability, and model monitoring.
Experience with enterprise‑grade AI security, governance, and responsible AI practices.
Experience working in Agile/Scrum environments.