Job Summary :

IBM is seeking an experienced Senior AI Copilot Engineer to lead the design, development, and deployment of enterprise-grade AI copilot solutions. The role focuses on leveraging advanced AI/ML technologies, including large language models (LLMs), to enhance productivity, automate workflows, and drive innovation across business units. The ideal candidate will bring strong technical expertise along with the ability to work in complex, client-facing environments.

AI Copilot Engineer :

Key Responsibilities :

- Lead the architecture, design, and implementation of AI copilot solutions using LLMs and generative AI technologies

- Develop and deploy scalable AI copilots integrated with enterprise platforms such as Microsoft 365 Copilot, GitHub Copilot, and IBM Watsonx

- Build and optimize Retrieval-Augmented Generation (RAG) pipelines and prompt engineering strategies

- Integrate AI solutions with enterprise applications, APIs, and data platforms

- Ensure compliance with IBMs data security, governance, and Responsible AI standards

- Collaborate with global stakeholders, clients, and cross-functional teams to identify high-impact use cases

- Mentor junior engineers and drive best practices in AI engineering and solution design

- Monitor model performance, manage lifecycle, and continuously optimize solutions

- Support pre-sales, solutioning, and client demonstrations when required

Required Skills & Qualifications :

- Bachelors or Masters degree in Computer Science, AI, Data Science, or related field

- 7-12+ years of experience in software development, with strong exposure to AI/ML and enterprise solutions

- Hands-on experience with LLMs and platforms such as Azure OpenAI, OpenAI, or Hugging Face

- Strong expertise in Python and/or JavaScript, along with API and microservices architecture

- Experience with cloud platforms, preferably Microsoft Azure (including Azure AI services)

- Deep understanding of NLP, prompt engineering, and LLM optimization techniques

- Experience with RAG architectures, vector databases (e.g., FAISS, Pinecone), and semantic search

- Familiarity with DevOps/MLOps practices, CI/CD pipelines, and containerization (Docker, Kubernetes)

- Strong understanding of enterprise security, compliance, and data governance