AI Engineer

Description GSPANN is hiring an AI Engineer to design, build, and scale AI-driven applications using Python, Microsoft Copilot Studio, and Azure AI services. The role involves collaborating with data scientists and engineers to operationalize machine learning models, build robust data pipelines, and deploy reliable, secure AI solutions.

Role and Responsibilities

Design, develop, and maintain artificial intelligence (AI)–driven applications using Microsoft Copilot Studio and Azure AI Foundry.

Partner with data scientists and engineers to operationalize machine learning (ML) models into scalable, production-ready solutions.

Build and optimize data pipelines to support AI workloads and model training at scale.

Deploy AI models and monitor their performance to ensure reliability, scalability, and security in production environments.

Develop application programming interfaces (APIs) and integrations that connect AI solutions with enterprise business applications.

Implement monitoring, automation, and governance to maintain AI systems throughout their lifecycle.

Engage with business stakeholders to understand use cases and deliver AI solutions that drive measurable business outcomes.

Document architectures, methodologies, and best practices to promote knowledge sharing across teams.

Align AI and data engineering initiatives with organizational goals and strategic priorities.

Collaborate across functions to maximize the adoption and impact of AI-driven solutions.

Ensure deployed solutions remain scalable, maintainable, and secure.

Take ownership of identifying business challenges and developing AI-based solutions proactively.

Explore emerging AI technologies and platforms to enhance solution capabilities continuously.

Skills and Experience

Proven experience in data engineering, AI solution development, and machine learning model deployment.

Strong programming skills in Python, with hands-on experience using ML frameworks such as Scikit-learn, PyTorch, and TensorFlow.

Practical experience with Azure AI services, including Azure OpenAI, Azure AI Foundry, and Microsoft Copilot Studio.

Solid understanding of data pipelines, Extract, Transform, Load (ETL) and Extract, Load, Transform (ELT) processes, and orchestration tools such as Azure Data Factory (ADF), Databricks, Azure Synapse, or Apache NiFi.

Familiarity with API development, microservices architecture, and cloud-native application design.

Knowledge of Machine Learning Operations (MLOps), Continuous Integration/Continuous Deployment (CI/CD) pipelines, and model lifecycle management.

Experience working with both structured and unstructured data, including text and image datasets.

Strong analytical and problem-solving skills, with the ability to translate business requirements into technical solutions.

Master’s degree in Computer Science, Data Engineering, Artificial Intelligence, or a related field; certifications in cloud AI services, machine learning, or MLOps are an advantage.