AI Engineer

Key Responsibilities

• Design, develop, and deploy AI-powered applications in production environments using Python or Node.js.
• Build and implement agentic AI solutions, multi-agent systems, and intelligent workflow orchestration.
• Develop context engineering strategies, prompt orchestration, grounding techniques, and memory management capabilities.
• Implement Model Context Protocol (MCP) and integrate AI tools with external systems and enterprise applications.
• Design and develop RAG-based solutions using vector databases, embeddings, and semantic search.
• Leverage Azure AI services, Azure AI Foundry, Azure OpenAI, or equivalent AI platforms to build and deploy intelligent applications.
• Implement AI evaluation frameworks, observability mechanisms, and governance practices.
• Ensure responsible AI implementation, reliability, scalability, and performance of AI-powered solutions.
• Collaborate with engineering, product, and business teams to translate requirements into effective AI solutions.
• Continuously evaluate emerging AI technologies, frameworks, and tools to improve development efficiency and solution capabilities.
• 5+ years of professional software engineering experience.
• Strong programming expertise in Python or Node.js.
• Hands-on experience building, deploying, and maintaining AI-powered applications in production.
• Experience with agentic frameworks, multi-agent architectures, and AI workflow orchestration.
• Strong understanding of context engineering, prompt orchestration, grounding techniques, and memory management.
• Practical experience implementing MCP (Model Context Protocol) and AI tool integration patterns.
• Strong knowledge of RAG architectures, vector databases, embeddings, and semantic search.
• Experience with Azure AI services, Azure AI Foundry, Azure OpenAI, or equivalent AI platforms.
• Understanding of AI evaluation, observability, governance, and responsible AI practices.
• Excellent communication and collaboration skills, with the ability to work across technical and business teams.
• Python
• AI-Powered Application Development
• Generative AI
• Agentic AI
• AI Workflow Orchestration
• Node.js
• Multi-Agent Systems
• MCP (Model Context Protocol)
• Retrieval-Augmented Generation (RAG)
• Vector Databases
• Embeddings and Semantic Search
• Azure AI Foundry
• Azure OpenAI
• AI Evaluation and Observability
• Responsible AI and Governance

Required Skills and Qualifications

Must-Have Skills

Good-to-Have Skills

Qualifications

• Key Responsibilities
• Design, develop, and deploy AI-powered applications in production environments using Python or Node.js.
• Build and implement agentic AI solutions, multi-agent systems, and intelligent workflow orchestration.
• Develop context engineering strategies, prompt orchestration, grounding techniques, and memory management capabilities.
• Implement Model Context Protocol (MCP) and integrate AI tools with external systems and enterprise applications.
• Design and develop RAG-based solutions using vector databases, embeddings, and semantic search.
• Leverage Azure AI services, Azure AI Foundry, Azure OpenAI, or equivalent AI platforms to build and deploy intelligent applications.
• Implement AI evaluation frameworks, observability mechanisms, and governance practices.
• Ensure responsible AI implementation, reliability, scalability, and performance of AI-powered solutions.
• Collaborate with engineering, product, and business teams to translate requirements into effective AI solutions.
• Continuously evaluate emerging AI technologies, frameworks, and tools to improve development efficiency and solution capabilities.
• Required Skills and Qualifications
• 5+ years of professional software engineering experience.
• Strong programming expertise in Python or Node.js.
• Hands-on experience building, deploying, and maintaining AI-powered applications in production.
• Experience with agentic frameworks, multi-agent architectures, and AI workflow orchestration.
• Strong understanding of context engineering, prompt orchestration, grounding techniques, and memory management.
• Practical experience implementing MCP (Model Context Protocol) and AI tool integration patterns.
• Strong knowledge of RAG architectures, vector databases, embeddings, and semantic search.
• Experience with Azure AI services, Azure AI Foundry, Azure OpenAI, or equivalent AI platforms.
• Understanding of AI evaluation, observability, governance, and responsible AI practices.
• Excellent communication and collaboration skills, with the ability to work across technical and business teams.
• Must-Have Skills
• Python
• AI-Powered Application Development
• Generative AI
• Agentic AI
• AI Workflow Orchestration
• Good-to-Have Skills
• Node.js
• Multi-Agent Systems
• MCP (Model Context Protocol)
• Retrieval-Augmented Generation (RAG)
• Vector Databases
• Embeddings and Semantic Search
• Azure AI Foundry
• Azure OpenAI
• AI Evaluation and Observability
• Responsible AI and Governance