AI Engineer

• Lead the technical design and implementation of end-to-end ML/AI solutions, from problem definition through production deployment and monitoring
• Define architectures and pipelines for Machine Learning, Computer Vision, and Generative AI, including RAG, embeddings, and agentic systems
• Contribute hands-on to model development, feature engineering, training, validation, and inference services
• Ensure engineering best practices, including model versioning, experiment tracking, MLOps/LLMOps, CI/CD, and observability
• Work with Data Engineers, MLOps, Product, and business stakeholders to ensure technical and functional alignment
• Support pre-sales activities and solution definition, contributing to technical proposals and estimates
• Promote component reuse, the creation of accelerators, and technical team mentoring

Tech Lead – ML/AI Engineering

• Develop and maintain scalable web applications using React and Next.js
• Design, develop and maintain APIs and backend services using Node.js
• Take ownership of implementing new features and technical improvements
• Collaborate closely with product and design teams to translate requirements into effective technical solutions
• Contribute to technical decisions, code quality and development best practices
• Integrate AI tools and capabilities into products and development workflows
• Design and implement automations and AI-assisted solutions
• Identify opportunities where AI can improve existing products, processes and workflows

Fullstack Developer – AI-Driven

• Design and implement lean, fit-for-purpose AI/LLM solutions, balancing quality, performance and cost
• Design, build and deploy AI-powered features across Shape App and Channels
• Work with product teams to translate user needs into AI opportunities and technical requirements
• Own the AI feature lifecycle from exploration and prototyping through production deployment and iteration
• Integrate AI capabilities into applications using prompt engineering, model selection, fine-tuning and evaluation
• Contribute production-grade code alongside other engineers
• Collaborate with SREs on infrastructure, observability, scaling, reliability and security
• Continuously explore developments in LLMs and generative AI with a product-first mindset
• Act as the go-to expert on AI/LLMs and help shape the company’s AI capability

• Develop, problem-solve, manage, and interact with multidisciplinary teams
• Create innovative digital products that improve and simplify people's lives
• Build orchestration and backend APIs using .NET/C#
• Work with Azure OpenAI, OpenAI, ChatGPT-class models, and generative AI pipelines
• Implement summarisation, extraction, filtering, and speech-to-text/transcription solutions
• Apply RAG and AI search patterns
• Use Agentic AI tools to accelerate code development, refactoring, and complex debugging
• Understand and work with Transformer-based model architectures and Machine Learning principles
• Deploy or integrate AI models into production APIs, pipelines, or backend systems
• Collaborate with engineering and product development teams on global projects

AI Engineer – .NET, Azure AI

• Own the quality of AI-generated visual content, creating realistic, attractive and consistent images of models/personas
• Continuously improve realism, visual polish, approval rate and business performance
• Build and optimize scalable generative AI pipelines using Nano Banana Pro, Flux, ChatGPT, ComfyUI, WaveSpeed and other AI platforms
• Automate content production at scale through batch generation and processing workflows with ComfyUI, n8n, APIs, simple scripts and vibecoding
• Define the technical direction for AI image generation and align different content streams
• Establish best practices and help transition from one-off generation to a reliable production system
• Explore and test new AI models, tools and techniques
• Evaluate business value and implement solutions that improve speed, quality, scalability or cost efficiency

Lead AI Generative Designer

• Design and implement serverless and cloud-native architectures on AWS
• Build and deploy Generative AI applications using Amazon Bedrock, foundation models, Knowledge Bases, Agent capabilities, guardrails, and related AWS services
• Develop AI applications and services using Python and Boto3
• Design and implement production-grade Retrieval-Augmented Generation solutions using Amazon OpenSearch, Bedrock Knowledge Bases, vector search technologies, and LLMs
• Design and optimise RAG pipelines, including chunking strategies, retrieval optimisation, metadata filtering, and context management
• Implement semantic search solutions using Amazon OpenSearch
• Design and build agent-based architectures using Bedrock Agents and AgentCore capabilities
• Develop prompt engineering frameworks and reusable prompting strategies
• Implement LLM evaluation methodologies, including LLM-as-a-Judge and automated evaluation frameworks
• Design model routing and inference optimisation strategies
• Apply GenAI observability, monitoring, and operational best practices
• Contribute to AI governance, evaluation, and responsible AI initiatives
• Support the industrialisation of AI solutions into scalable production environments
• Collaborate with Cloud Engineers, Data Engineers, Architects, and client stakeholders
• Contribute to AI engineering best practices, standards, and reusable frameworks

AI Engineer jobs in Portugal

Tech Lead – ML/AI Engineering

Fullstack Developer – AI-Driven

AI Engineer

AI Engineer – .NET, Azure AI

Lead AI Generative Designer

Senior AWS AI Engineer