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Gen ai engineer - remote / telecommute

Darwin
Cynet systems Inc
Posted: 25 March
Offer description

Job Overview:
Pay Range: $55hr - $60hr

Responsibilities:

* Develop and implement Generative AI solutions using frameworks such as Microsoft Agent Framework (AutoGen), Semantic Kernel, and Copilot Studio.
* Build and deploy machine learning and AI models as defined by solution architects.
* Work across all phases of the Software Development Life Cycle (SDLC) including requirements, design, development, testing, deployment, and maintenance.
* Develop scalable AI applications leveraging Azure AI Foundry and cloud PaaS services.
* Integrate AI/ML models into enterprise applications and workflows.
* Perform data preprocessing, feature engineering, and model optimization.
* Collaborate with cross-functional teams to translate business requirements into AI-driven solutions.
* Ensure code quality, testing, and proper documentation for all deliverables.
* Monitor model performance and continuously improve solutions.
* Provide regular updates on progress, risks, and deliverables to stakeholders.

Required Qualifications:

* Hands-on experience with Azure AI Foundry and Azure cloud services (PaaS).
* Strong programming skills in Python including libraries such as NumPy, Pandas, Matplotlib, and Scikit-learn.
* Experience with Generative AI and agent frameworks such as AutoGen, Semantic Kernel, Azure OpenAI.
* Understanding of machine learning fundamentals including supervised and unsupervised learning, neural networks, and NLP.
* Familiarity with GenAI tools such as Hugging Face Transformers, OpenAI APIs, MCP Server, and diffusion models.
* Experience working across SDLC with strong coding, testing, and documentation practices.
* Strong analytical and problem-solving skills.
* Good communication and collaboration abilities.

Preferred Qualifications:

* Experience with multi-agent frameworks such as AutoGen or LangGraph.
* Knowledge of Retrieval-Augmented Generation (RAG), vector databases, and prompt engineering.
* Understanding of AI safety, guardrails, and responsible AI practices.
* Exposure to MLOps including model versioning, deployment, and monitoring.
* Microsoft Azure certifications.

Key Skills:

* Generative AI & Agentic AI Development.
* Azure AI & Cloud Services.
* Python & Machine Learning Libraries.
* NLP & Deep Learning Fundamentals.
* RAG & Vector Databases.
* MLOps & Deployment Pipelines.
* SDLC & Software Engineering Practices.
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