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AI Solution Expert

Job Description - AI Solution Expert


Who we are


 


We are looking for an AI Solutions Expert with deep hands-on expertise in designing, validating, and implementing enterprise-grade AI solutions. You will work closely with engineering teams, architects, and business stakeholders to translate complex requirements into robust, scalable, and production-ready AI solutions.


This is a highly technical and hands-on role, combining AI solution architecture, prototyping, implementation, technical validation, and complex problem-solving, with a strong focus on Generative AI and agentic systems.


 


What you'll be doing


 



  • Design and validate enterprise AI and Generative AI architectures, ensuring scalability, reliability, security, and maintainability

  • Build prototypes and Proofs of Concept (PoCs) to validate technical approaches before production implementation

  • Design and implement RAG solutions, AI agents, knowledge architectures, tool integrations, and AI workflows

  • Support engineering teams with hands-on implementation, architecture reviews, troubleshooting and deployment

  • Diagnose complex end-to-end issues across AI models, applications, integrations, data/knowledge layers and platform components

  • Establish reusable AI design patterns, reference architectures, technical standards and best practices

  • Implement approaches for LLM evaluation, monitoring, tracing, observability and solution quality

  • Identify whether technical challenges are caused by the solution design, architectural limitations, model behavior, or missing platform capabilities

  • Collaborate with developers, architects, product teams, and stakeholders to drive AI solutions from concept to production



What you'll bring along


 



  • Degree in Computer Science, Engineering or equivalent experience

  • Strong, demonstrable hands-on experience building AI/GenAI solutions in production environments

  • Deep understanding of LLMs, Generative AI, AI agents/agentic workflows, RAG, embeddings, vector search and knowledge retrieval

  • Experience designing and implementing enterprise-grade AI solution architectures

  • Strong experience with Python and AI/LLM development frameworks

  • Practical experience with frameworks and platforms such as LangChain, LangGraph, Semantic Kernel, LlamaIndex, Azure AI Foundry, Azure OpenAI, AWS Bedrock, or equivalent technologies

  • Experience integrating AI solutions with APIs, enterprise systems, databases, vector databases and external tools/services

  • Knowledge of LLM evaluation, prompt engineering, guardrails, observability, tracing, monitoring and performance optimization

  • Strong troubleshooting skills across complex, distributed AI solutions

  • Ability to move comfortably between architecture-level decisions and hands-on implementation/code reviews

  • Strong communication skills and the ability to explain complex AI concepts to both technical and non-technical stakeholders


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