Verified 5 days ago
Azure AI Co-Pilot Engineer
About the role
Azure AI Co‑Pilot Engineer at Onebridge will design, build, and deploy AI‑powered copilots using Microsoft Azure’s AI ecosystem. The role focuses on Azure AI Foundry, Copilot Studio, and Azure OpenAI to create scalable, secure, and high‑performance solutions that integrate with business workflows. The engineer will collaborate with stakeholders to translate requirements into technical specifications, fine‑tune large language models, and apply prompt‑engineering best practices. Responsibilities include building conversational and generative AI copilots, orchestrating CI/CD pipelines with Azure DevOps, and ensuring data protection and secure API development. The position requires strong Python programming, SQL knowledge, and familiarity with ML libraries and UI frameworks such as Streamlit or JavaScript. Candidates should have at least 2–3 months of hands‑on experience with Azure AI services and a passion for emerging AI technologies. The role is hybrid, with onsite work two days a week in Bangalore, and offers a dynamic, collaborative environment for advancing AI solutions across healthcare, finance, and government sectors.
What you’ll do
- Design and implement AI‑powered solutions with Azure AI Foundry, Copilot Studio, Azure OpenAI
- Build and customize copilots that integrate with business workflows
- Translate business requirements into technical specifications
- Fine‑tune AI models and apply prompt‑engineering best practices
- Collaborate with stakeholders and global teams
- Maintain CI/CD pipelines and secure API development
What you’ll bring
- 2–3 months hands‑on experience with Azure AI Foundry, Copilot Studio, Azure AI services
- Solid Python programming and SQL knowledge
- Familiarity with ML libraries and UI frameworks (Streamlit or JavaScript)
Nice to have
- Experience with LLMs, prompt engineering, Retrieval‑Augmented Generation (RAG)
- Familiarity with Azure DevOps, CI/CD pipelines, Git
- Knowledge of secure API/web service development and data protection best practices