AI / LLM engineer
act digital EMEA - Alter Solutions · Lisbon, Lisbon, Portugal
- Hybrid
- Other
- $120,000 / year
- Lisbon, Lisbon, Portugal
Job highlights
- Develop and deploy LLM-based AI solutions.
- Focus on European data sovereignty and compliance.
- Implement RAG pipelines and fine-tune models.
- Utilize Python, PyTorch, Hugging Face ecosystems.
- Containerize and deploy AI applications using Docker.
About the role
About act digital
act digital is an international consulting and engineering group that supports its clients in their digital transformation projects. Present in 12 countries and with more than 5,600 employees, we leverage our expertise to address their challenges in software development, cybersecurity, data, cloud, and AI. Our ambition: to become the trusted technology partner of the most innovative companies, by designing and securing systems that enhance their performance and resilience. Joining act digital means becoming part of an agile and committed organization that works closely with its clients to turn ideas into concrete results, with pragmatism and high standards.Job Description
You will join our delivery center, working within a team of experts in software solution development. Your responsibilities will include:- Design, develop, and deploy AI solutions based on Large Language Models (LLMs) in secure and production-grade environments
- Select, evaluate, and integrate foundation models with a strong focus on European data sovereignty and compliance
- Implement Retrieval-Augmented Generation (RAG) pipelines using embeddings, vector databases, and optimized retrieval strategies
- Fine-tune and adapt models (e.g., LoRA, PEFT) to meet specific business and regulatory requirements
- Build and maintain scalable AI services and APIs using Python, PyTorch, and Hugging Face ecosystems
- Containerize and deploy AI applications using Docker and CI/CD pipelines in controlled environments
Profile / Requirements
What profile are we looking for for this position:- Must-have skills:
- Strong experience with LLMs / foundation models / transformers
- Very strong Python skills
- Experience with PyTorch, Hugging Face, APIs, and model integration
- Experience with RAG, embeddings, fine-tuning / LoRA
- Experience with Docker, Git, CI/CD, and production-oriented setups
- Solid understanding of data protection / GDPR, data sovereignty, and secure model usage
- Experience with security topics such as prompt injection, data leakage, and access control
- Ability to implement and operate models in controlled European environments
- Requirements:
- Select, integrate, and adapt AI models with a focus on European sovereignty
- Build secure and traceable AI solutions for enterprise environments
- Evaluate models in terms of quality, risk, privacy, and operability
- Document model usage, data sources, limitations, and risks
- Work closely with security, privacy, architecture, and business teams
- Strong focus on productive delivery, not only PoCs or prompt engineering
Key skills/competency
- AI / LLM Engineer
- Large Language Models (LLMs)
- Foundation Models
- Transformers
- Python
- PyTorch
- Hugging Face
- Retrieval-Augmented Generation (RAG)
- Fine-tuning
- Docker
Skills & topics
- AI Engineer
- LLM Engineer
- Large Language Models
- Python
- PyTorch
- Hugging Face
- RAG
- Docker
- CI/CD
- Data Sovereignty
- GDPR
- Transformers
- Foundation Models
- Model Integration
- Fine-tuning
- LoRA
- APIs
- Embeddings
- Vector Databases
- Production Deployment
How to get hired
- Tailor your resume: Highlight Python, LLM, RAG, and containerization skills.
- Showcase European data sovereignty experience: Emphasize GDPR and secure model usage.
- Prepare for technical interviews: Expect questions on model integration, fine-tuning, and APIs.
- Demonstrate production deployment experience: Discuss your work with Docker, CI/CD, and secure environments.
- Understand AI security: Be ready to discuss prompt injection and data leakage.
Technical preparation
Master Python for AI development.,Build RAG pipelines with embeddings.,Practice LoRA and PEFT fine-tuning.,Deploy models using Docker and CI/CD.
Behavioral questions
Describe a complex AI project you delivered.,How do you ensure data privacy in AI?,How do you collaborate with security teams?,Explain your approach to model risk evaluation.
Frequently asked questions
- What specific experience is required for the AI / LLM Engineer role at act digital?
- For the AI / LLM Engineer position at act digital, strong Python skills are essential, alongside significant experience with Large Language Models (LLMs), foundation models, and transformers. You should also have practical experience with PyTorch, Hugging Face, APIs, model integration, RAG, embeddings, and fine-tuning techniques like LoRA. Familiarity with Docker, Git, CI/CD, and production-oriented setups, as well as a solid understanding of data protection (GDPR) and European data sovereignty, are also crucial.
- How important is European data sovereignty for this AI / LLM Engineer role?
- European data sovereignty is a critical focus for this AI / LLM Engineer role at act digital. You will be expected to select, evaluate, and integrate foundation models with a strong emphasis on compliance with European data protection regulations and sovereignty requirements. Building secure and traceable AI solutions within controlled European environments is a key aspect of the job.
- What are the main responsibilities of an AI / LLM Engineer at act digital?
- As an AI / LLM Engineer at act digital, your primary responsibilities will involve designing, developing, and deploying AI solutions leveraging Large Language Models (LLMs). This includes implementing RAG pipelines, fine-tuning models, building scalable AI services and APIs using Python and PyTorch, and containerizing applications with Docker for production environments, all while adhering to security and data sovereignty standards.
- What technologies will I use as an AI / LLM Engineer at act digital?
- You will primarily work with Python, PyTorch, and the Hugging Face ecosystem. Key technologies include Large Language Models (LLMs), foundation models, transformers, Retrieval-Augmented Generation (RAG), embeddings, vector databases, and fine-tuning techniques like LoRA. For deployment and operations, you'll use Docker, Git, and CI/CD pipelines.
- Does act digital focus on production-ready AI solutions for this role?
- Yes, act digital has a strong focus on productive delivery for this AI / LLM Engineer role. While foundational knowledge is important, the emphasis is on implementing and operating models in controlled European environments, building secure and traceable AI solutions for enterprise use, and ensuring production-grade deployments rather than just Proofs of Concept (PoCs) or prompt engineering.