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 (Po.

Cs) 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 Lang.

Chain, Lang. Graph, Semantic Kernel, Llama. Index, 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