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