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.