Gen AI Engineer - Remote / Telecommute

Generative Ai Solutions Developer

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.