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Seeking an experienced AI Full Stack Developer to design, develop, and deploy enterprise AI applications, intelligent agents, and data-driven solutions leveraging Generative AI, Azure AI services, ... Show more
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The average salary range is between $ 109,688 and $ 189,588 year , with the average salary hovering around $ 119,700 year .
The average salary range is between $ 102,442 and $ 150,000 year , with the average salary hovering around $ 120,000 year .
Seeking an experienced AI Full Stack Developer to design, develop, and deploy enterprise AI applications, intelligent agents, and data-driven solutions leveraging Generative AI, Azure AI services, and modern data platforms.
Key Responsibilities
• Build AI-powered applications and agentic workflows.
• Develop RAG-based knowledge, search, and document intelligence solutions.
• Design and develop backend services, APIs, and integration components.
• Integrate AI solutions with enterprise data platforms and business applications.
• Develop data pipelines and AI workflows.
• Deliver scalable, production-ready AI solutions.
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Must-Have Skills
1. Azure AI Foundry & Azure OpenAI
2. RAG, Vector Databases, Prompt Engineering & Agentic AI Frameworks (LangChain, Semantic Kernel, CrewAI)
3. Python
4. Snowflake, SQL & Data Integration
5. Enterprise API / Microservices Development
________________________________________
Nice-to-Have Skills
• Databricks
• Snowflake Cortex / Cortex Agents
• Azure ML
• MLOps / Model Monitoring
• React/Angular
• Manufacturing, Supply Chain, or Life Sciences experience
________________________________________
Experience
• Bachelor's or Master's degree in Computer Science, AI, Data Science, or related field.
• 5-10 years of software engineering experience.
• 2+ years of hands-on experience building GenAI, Agentic AI, or AI-powered enterprise applications.
• Experience integrating AI solutions with cloud data platforms and enterprise systems.
Ideal Candidate
A hands-on AI engineer capable of independently building AI applications and intelligent agents using Azure AI Foundry, integrating with Snowflake-based data platforms, developing AI workflows and data pipelines, and taking solutions from design through production deployment.
