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AI Solution Expert / AI Developer

Lisbon

Job description

We are looking for a Senior AI Solution Expert / AI Developer for a hybrid project in Lisbon.

About the Role

You will be joining a team focused on designing, implementing, and enabling AI capabilities that support real business use cases. Your main focus will be on LLM-based solutions, Retrieval-Augmented Generation (RAG), knowledge ingestion, semantic search, document intelligence, AI evaluation, grounding, and traceability — all built on Azure-based AI services.

This is not an end-to-end fullstack application delivery role. You will act as an AI capability enabler, translating business needs and data sources into secure, scalable, reusable and governed AI solution components, while guiding and supporting product and development teams on how AI capabilities can be integrated into applications and business workflows.

Main Responsibilities

  • Translate business needs, data sources and AI opportunities into feasible AI solution concepts, implementation approaches, prototypes, MVPs and reusable AI capabilities.
  • Design and implement AI solution components using Azure AI Foundry, Azure OpenAI, Azure AI Search, Azure ML, Document Intelligence, Cosmos DB, Azure Functions, APIs and related cloud services.
  • Implement LLM-based and RAG solutions, including prompt engineering, embeddings, indexing, knowledge ingestion, semantic search, grounding, source traceability, evaluation and answer validation.
  • Provide AI delivery support across the use case lifecycle — from discovery, feasibility assessment and technical option definition through to implementation support, evaluation, deployment readiness, monitoring concepts and reusable capability creation.
  • Support and coach product and development teams on AI feasibility, solution options, technical trade-offs, reuse opportunities, model behaviour, cost implications, responsible AI practices and production readiness.
  • Build modular AI components, reusable knowledge ingestion pipelines, orchestration layers, MCP/API-based integration patterns, evaluation mechanisms and cross-solution AI capability building blocks.
  • Ensure explainability, traceability, cost awareness, responsible AI, security and production readiness across all delivered solutions.
  • Work flexibly with GitHub Copilot and other AI-assisted development tooling to accelerate implementation, testing, documentation and knowledge creation.


Requirements

  • Senior level: AI Solution Design and Implementation for Business Use Cases.
  • Senior level: LLMs, Embeddings, Indexing and RAG Systems.
  • Senior level: Azure AI Foundry / Azure OpenAI / Azure AI Search Implementation.
  • Mid level: Machine Learning Concepts, AI Evaluation and Model Lifecycle Awareness.
  • Mid level: Knowledge Graphs, Semantic Models and Domain Reasoning.
  • Mid level: Azure AI Search / Vector Search / Semantic Retrieval.
  • Mid level: Cosmos DB and Cloud Data Architecture for AI Solutions.
  • Mid level: AI Cost Estimation, Model Selection and Architecture Decision Matrix.
  • Mid level: MCP / API Integration Patterns for AI Services and Reusable Capabilities.


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