Qureos Mentor

Quality Standards for Information Technology - QSIT

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 Job Responsibilities:
 
 
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 Design, develop, and optimize AI/ML solutions for real business use cases.
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 Build and evaluate machine learning, deep learning, and generative AI models.
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 Analyze and preprocess structured and unstructured data to support model development and solution quality.
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 Validate model performance, reliability, scalability, and production readiness.
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 Ensure AI solutions align with enterprise standards for maintainability, quality, and governance.
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 Design and implement LLM-based and Generative AI solutions, including RAG pipelines, prompt engineering, retrieval optimization, and evaluation.
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 Work with embeddings, vector search, reranking, and enterprise knowledge integration patterns.
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 Support use cases such as document intelligence, AI assistants, chatbots, search augmentation, and decision-support solutions.
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 Own AI solution delivery from requirement analysis through deployment, integration, and handover.
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 Collaborate with software, data, and platform teams to integrate AI capabilities into enterprise platforms and APIs.
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 Support monitoring, optimization, and post-go-live improvement of AI services.
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 Apply MLOps / LLMOps practices for reproducibility, deployment automation, monitoring, and lifecycle management.
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 Support technical proposal development, bid responses, and client-facing AI solution discussions when required.
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 Contribute to technical presentations, solution write-ups, and AI capability positioning.
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 Provide technical insight during opportunity shaping and feasibility assessments.
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 Required Qualifications:
 
 
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 Bachelor&rsquo;s in Computer Science, AI, Data Science, Computer Engineering, or related field.
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 From 4&ndash;6 years of hands-on experience delivering end-to-end AI/ML solutions in real business environments (not just PoCs/research).
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 Strong Python skills; hands-on with PyTorch, TensorFlow, and Scikit-learn.
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 Experience in data preprocessing, feature engineering, model evaluation, and optimization.
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 Practical experience with Generative AI, LLMs, RAG, embeddings, and vector databases.
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 Familiar with prompt engineering, LLM evaluation, guardrails, and inference optimization.
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 Experience with MLOps/LLMOps (deployment, monitoring, versioning, lifecycle).
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 Cloud experience: Azure AI / Azure OpenAI preferred; AWS/GCP a plus.
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 Experience with APIs, microservices, enterprise integration, and Docker/containers.
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 Experience in domains like NLP, document intelligence, CV, forecasting, recommendations, or conversational AI.
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 Strong analytical, communication, and cross-functional collaboration skills; leadership/mentoring mindset.
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 Proven delivery of deployed AI/ML solutions.
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 Provide project examples with: domain/client, AI approach, role, and deployment environment.
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 Show involvement in deployment, handover, and post-go-live support/optimization.
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 </ul>
 
 
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Senior AI Engineer

Join Quality Standards for Information Technology - QSIT and explore 1   exciting career opportunities. They're hiring for various roles with options for remote or on-site work. Apply today and become part of their innovative team.

Quality Standards for Information Technology - QSIT

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Senior AI Engineer