GenAI Engineer
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Role details
Tech stack
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Job description
- Design, develop, and deploy AI agents and agentic workflows using modern Generative AI frameworks
- Build scalable solutions leveraging Large Language Models (LLMs), retrieval-augmented generation (RAG), orchestration frameworks, and autonomous agents.
- Develop and optimize multi-step AI workflows that integrate with enterprise systems, APIs, and business processes.
- Collaborate with product, engineering, and business stakeholders to identify AI use cases and deliver production-ready solutions.
- Evaluate emerging AI technologies, frameworks, and tools to improve development efficiency and solution effectiveness.
- Ensure AI solutions meet enterprise standards for scalability, security, performance, and maintainability.
Requirements
We are seeking a highly skilled Generative AI Engineer to design, build, and deploy intelligent AI agents that solve complex business challenges. The ideal candidate will have hands-on experience with modern AI development lifecycle tools, agentic frameworks, and enterprise AI platforms, with the ability to take solutions from concept through production deployment., * Experience with Microsoft Fabric and in building and deploying AI agents on Azure AI Foundry.
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Strong hands-on experience with at least one AI-assisted development platform:
- Claude Code
- GitHub Copilot
- Cursor
- Windsurf
-
Slingshot
- Experience building, testing, and deploying agentic AI solutions in enterprise environments.
- Solid understanding of Large Language Models (LLMs), prompt engineering, AI workflow orchestration, tool calling, memory management, and agent architectures.
- Strong software engineering fundamentals with experience in API integration, system design, and application development.
- Preferred Qualifications
Proven experience designing and implementing AI agents using modern Generative AI frameworks such as:
- LangGraph
- LangChain
-
LangSmith
- Similar agent orchestration and observability frameworks
- Familiarity with cloud-native AI architectures and MLOps best practices.
- Experience integrating AI solutions with enterprise data platforms and business applications.
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Prepare application
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