Technical Lead

Generative AI & Agent Development

• Design, develop, and deploy enterprise-grade AI agents, copilots, and conversational applications.
• Implement multi-agent systems, tool-calling workflows, Retrieval-Augmented Generation (RAG) architectures, and prompt orchestration frameworks.
• Integrate AI solutions with Microsoft 365 technologies, including Teams, SharePoint, Outlook, Power Platform, Copilot Studio, and Microsoft Graph.
• Apply AI-assisted engineering practices to accelerate software delivery while maintaining code quality and security standards.
• Establish governance, monitoring, and evaluation frameworks for AI applications.

Machine Learning & Predictive Analytics

• Design and deploy predictive machine learning models for classification, regression, forecasting, and anomaly detection use cases.
• Build and maintain data pipelines supporting model development and deployment.
• Manage the end-to-end machine learning lifecycle, including feature engineering, training, validation, deployment, and monitoring.
• Collaborate with data engineering teams to develop scalable data solutions.

Backend Engineering

• Develop scalable APIs and backend services using Python frameworks such as FastAPI, Flask, or Django.
• Build maintainable, testable, and well-documented applications following modern software development practices.
• Participate in architecture reviews and technical design discussions.
• Support CI/CD implementation and cloud deployment strategies.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related discipline.
• 8+ years of professional software development experience.
• Strong proficiency in Python, including object-oriented programming, asynchronous programming, and API development.
• Experience developing Generative AI applications using modern LLM platforms and agent frameworks.
• Experience implementing RAG architectures and vector database solutions.
• Strong understanding of machine learning concepts and hands-on experience with scikit-learn, pandas, NumPy, and PyTorch or TensorFlow.
• Experience building REST APIs and production-ready data pipelines.
• Experience with Microsoft Azure and Microsoft 365 integration technologies.
• Knowledge of software architecture, security, scalability, and enterprise integration patterns.
• Experience using Git-based development workflows and AI-assisted coding tools.

Preferred Qualifications

• Experience with Java and Spring Boot.
• Experience with Docker, Kubernetes, and CI/CD pipelines.
• Familiarity with MLOps platforms such as MLflow, Kubeflow, or Azure Machine Learning.
• Experience building enterprise copilots and AI assistants.
• Knowledge of AI evaluation frameworks, guardrails, observability, and responsible AI practices.

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