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Senior AI Software Engineer

Porto

Job description

Project context

We are looking for a Senior AI Software Engineer to join a Framework and Research team developing shared services and technical components used across several product areas.

The role combines applied Machine Learning, Generative AI and software engineering. You will design, fine-tune, evaluate and deploy AI/ML models, develop LLM-based solutions and integrate AI capabilities into cloud-native applications.

You will work across the full AI solution lifecycle, from proof of concept and data analysis through to production deployment, governance and continuous improvement.

Goals and deliverables

Translate business requirements into functional applications and AI/ML solutions.
Design, fine-tune, evaluate and deploy AI/ML models for real-world use cases.
Develop and refine prompts for LLM-based applications.
Experiment with model parameters such as temperature and top-p.
Work with GPT, Transformers, Hugging Face and related AI frameworks.
Build proofs of concept using Jupyter notebooks and similar research tools.
Analyse datasets and assess model performance using suitable evaluation methods.
Develop AI pipelines covering data preparation, model execution, testing and deployment.
Design and integrate AI capabilities into business applications and shared technical services.
Work with cloud AI services such as AWS SageMaker, AWS Bedrock, Azure Machine Learning or equivalent services.
Apply AI governance, guardrails, auditing and secure usage practices.
Protect data and APIs through appropriate security and privacy controls.
Design cloud-native architectures for AI and software solutions.
Support production deployment, observability and ongoing model or service improvements.
Collaborate with Product Owners, software engineers, data specialists and other stakeholders.
Conduct code reviews and contribute to technical standards.
Mentor team members and share knowledge across the engineering community.
Document AI approaches, model decisions, system architecture and operational procedures.

Requirements

Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science or a related field.
At least 2 years of professional experience in Machine Learning, Generative AI or Data Science.
Strong Python development experience.
Hands-on experience with AI/ML model development, fine-tuning, evaluation and deployment.
Experience with prompt engineering and LLM frameworks or tools.
Practical knowledge of GPT, Transformers, Hugging Face or equivalent technologies.
Experience working with AWS AI services, such as SageMaker or Bedrock, or equivalent Azure services.
Good knowledge of software development, databases and system design.
Experience building and integrating AI solutions into applications or technical platforms.
Understanding of AI governance, guardrails, auditing, API security and data privacy.
Excellent problem-solving skills.
Experience working in Agile or Scrum environments.

Nice to have:

Experience building production-grade AI solutions.
Experience across multiple model families, including non-LLM Machine Learning models.
Exposure to MLOps, experiment tracking, model versioning and model monitoring.
Experience with AI governance frameworks.
Cloud or AI certifications from AWS or Microsoft Azure.
Experience with Docker, Kubernetes and DevOps or CI/CD pipelines.
Experience with C# and .NET/.NET Core.
Experience with Java and Spring Boot.
Experience with Jupyter, Databricks, MLflow or similar tools.
Experience working with regulated, sensitive or business-critical data.

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