Aes – DE - Generative AI Application Developers

As a Generative AI Developer, you will be responsible for developing, integrating, and optimizing Generative AI solutions that enhance business processes, automate workflows, and improve user experiences. You will collaborate with cross-functional teams, including product managers, data scientists, architects, and business stakeholders, to build innovative AI-driven applications using cutting-edge AI platforms and cloud technologies.

The role involves developing AI-powered chatbots, copilots, intelligent assistants, document processing solutions, knowledge management systems, and workflow automation applications while ensuring security, reliability, and scalability.

• Bachelor's or Master's degree in Computer Science, Information Technology, Artificial Intelligence, Data Science, or a related field.
• 3+ years of software development experience and 1+ years of hands-on experience with Generative AI technologies.
• Strong programming skills in Python, JavaScript, C#, or Java.
• Experience with Large Language Models (LLMs), prompt engineering, and AI application development.
• Hands-on experience with AI frameworks such as LangChain, Semantic Kernel, LlamaIndex, AutoGen, or LangGraph.
• Knowledge of REST APIs, Microservices, and cloud-native application development.
• Familiarity with vector databases such as Pinecone, Chroma, FAISS, Weaviate, or Azure AI Search.
• Experience with Azure OpenAI, OpenAI APIs, or similar AI platforms.
• Understanding of responsible AI, model governance, and AI security principles.
• Strong problem-solving, analytical, and communication skills.

Preferred Qualifications

• Microsoft Azure AI Engineer Associate (AI-102) or equivalent AI certification.
• Experience with Azure AI Foundry, Azure Machine Learning, and Azure Cognitive Services.
• Knowledge of MLOps, CI/CD pipelines, and containerization technologies such as Docker and Kubernetes.
• Experience building multi-agent AI systems and enterprise copilots.

Familiarity with DevOps practices and Agile development methodologies.

AI Solution Development

• Python on Azure, any good advanced knowledge on Agentic framework like MAF
• Build intelligent AI copilots, virtual assistants, and conversational AI solutions.
• Develop Retrieval-Augmented Generation (RAG) architectures for enterprise knowledge management.

AI Integration & Engineering

• MS graph api knowledge
• Integrate AI solutions with enterprise systems, APIs, databases, and business applications.
• Develop prompt engineering strategies and optimize prompts for performance and accuracy.
• Implement AI agents and orchestration frameworks using tools such as LangChain, Semantic Kernel, LangGraph, LlamaIndex, or similar platforms.

Model Optimization & Deployment

• Fine-tune foundation models where applicable and optimize model performance.
• Monitor AI solution effectiveness and continuously improve output quality.
• Deploy AI applications using cloud platforms such as Microsoft Azure, AWS, or Google Cloud.

Data Management & Security

• Build secure and compliant AI solutions while adhering to responsible AI principles.
• Ensure data privacy, governance, and regulatory compliance standards are met.
• Implement vector databases and embedding techniques for semantic search capabilities.

Collaboration & Innovation

• Collaborate with product teams to define AI use cases and business requirements.
• Stay current with emerging Generative AI technologies, frameworks, and industry trends.
• Contribute to AI best practices, architecture standards, and reusable components.