Senior AI Engineer

Senior AI Engineer

Job Summary

We are looking for an experienced and highly skilled Senior AI Engineer with 7+ years of professional experience to join our AI engineering team. The candidate will be responsible for designing, developing, deploying, and optimizing enterprise-grade AI and Machine Learning solutions using modern Microsoft technologies and cloud platforms.

The role requires strong hands-on expertise in Python, Azure, Azure OpenAI, Azure AI Agents, Microsoft Fabric, Machine Learning, Generative AI, and LLM-based applications. The candidate will work closely with engineering, data, and business teams to build scalable and production-ready AI solutions.

Key Responsibilities

• Design, develop, and deploy scalable AI/ML and Agentic AI solutions for enterprise applications.
• Build and integrate LLM-powered applications, AI agents, APIs, and intelligent automation solutions.
• Develop solutions using Azure AI Agents, Azure AI Services, Azure Machine Learning, and Microsoft Fabric.
• Design and implement AgentOps pipelines for data preparation, model development, evaluation, deployment, and monitoring.
• Work with Large Language Models (LLMs), prompt engineering, RAG, embeddings, vector search, and AI agents.
• Develop robust and scalable applications using Python and C#/.NET.
• Integrate AI capabilities with enterprise applications through REST APIs and cloud-native services.
• Work with Microsoft Fabric for data engineering, analytics, and AI/ML use cases.
• Implement model and application optimization techniques to improve performance, scalability, accuracy, and reliability.
• Collaborate with data engineers, software engineers, solution architects, and business stakeholders to translate requirements into technical solutions.
• Participate in technical design, architecture discussions, code reviews, testing, and production deployments.
• Implement CI/CD, version control, and deployment workflows using Git/GitHub and Azure DevOps.
• Troubleshoot production issues and provide technical solutions for AI/ML applications.
• Follow secure coding, cloud security, data governance, and enterprise development best practices.
• Mentor junior AI engineers and contribute to technical knowledge sharing within the team.
• Stay updated with emerging developments in Generative AI, Microsoft AI technologies, LLMs, and Machine Learning.

Qualifications

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Information Technology, Engineering, or a related field.
• 7+ years of professional experience in AI/ML, Machine Learning Engineering, Data Science, Software Engineering, or a related role.
• Strong hands-on experience in developing and deploying production-grade AI/ML solutions.
• Strong programming experience in Python.
• Good hands-on experience with C#/.NET and enterprise application development.
• Strong understanding of Machine Learning concepts, model evaluation, optimization, and deployment.
• Experience working with cloud-based AI and data platforms, preferably within the Microsoft Azure ecosystem.
• Strong analytical, problem-solving, communication, and collaboration skills.

Required Technical Skills

Microsoft & Azure Technologies

• Microsoft Azure
• Azure OpenAI Service
• Azure AI Services
• Azure Machine Learning
• Microsoft Fabric
• Azure Functions and other Azure cloud services
• Azure DevOps

AI / Machine Learning

• Machine Learning and Deep Learning fundamentals
• Generative AI and Large Language Models (LLMs)
• Prompt Engineering
• Retrieval-Augmented Generation (RAG)
• Embeddings and Vector Search
• AI Agents / Agentic AI
• Model evaluation and optimization
• AI/ML deployment and monitoring

Programming & Development

• Python Strong proficiency
• C#/.NET
• SQL
• REST APIs
• Git/GitHub
• Software development and debugging practices

Data & Cloud

• Microsoft Fabric
• Data processing and data pipelines
• Cloud architecture and services
• Data integration and API development

Preferred Skills

• Azure Agent Framework
• LangChain / LangGraph
• Azure AI Search
• Azure Data Factory
• Databricks
• Docker and containerization
• Kubernetes
• MLOps / LLMOps
• CI/CD pipelines
• Power BI
• Experience building enterprise AI agents and copilots
• Experience with vector databases and semantic search
• Knowledge of responsible AI, AI security, and governance