Technical Lead
Posted 14 Oct 2026
BranchFactor Summary
The original posting with the fluff stripped out
- Expected experience
- 8+ yrs
- Management level
- Individual contributor
- Employment
- Hybrid
Compensation
No salary listed for this role.
Role speciality
Artificial IntelligenceBackend EngineeringGenerative AIMachine Learning
Useful technologies
Azure Machine LearningCopilot StudioDjangoDockerFastAPIFlaskGitJavaKubeflowKubernetesMicrosoft 365Microsoft AzureMicrosoft GraphMLflowNumPyOutlookpandasPower PlatformPythonPyTorchscikit-learnSharePointSpring BootTeamsTensorFlow
Required qualifications
Field of studyComputer Science, Data Science, Engineering (or related)
Study levelBachelor's or higher
The Senior AI Engineer will lead the design and implementation of AI-powered applications, intelligent agents, predictive analytics solutions, and scalable backend services. This role requires expertise in Python development, machine learning, enterprise AI platforms, cloud technologies, and API architecture. You will collaborate with cross-functional teams to transform business requirements into secure, scalable, and production-ready solutions while ensuring alignment with enterprise governance and compliance standards.
Responsibilities
Key Responsibilities:
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.
Qualifications
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.