AI Solutions Engineer at Inetum

Lisbon, , Portugal -

Full Time

Start Date

Immediate

Expiry Date

11 Oct, 26

Salary

0.0

Posted On

13 Jul, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, Generative AI, RAG, LLM Integration, NLP, Machine Learning, API Development, DevOps, Kubernetes, CI/CD, Git, Prompt Engineering, Vector Databases, RPA, Agile, Software Engineering

Industry

IT Services and IT Consulting

Description

Company Description Inetum is a global leader in IT services, dedicated to delivering innovative solutions to our clients. We are committed to fostering a dynamic and inclusive work environment that values diversity, where creativity and collaboration can thrive. We are present in 19 countries and have more than 28,000 employees worldwide. If you are looking for a dynamic, innovative, and technology-driven company, Inetum is the place for you! Come be part of Inetum! Job Description Our client is a leading international financial institution undergoing a significant digital transformation journey. The organization is investing in innovative technologies, modern architectures, and data-driven solutions to enhance operational efficiency, agility, and time-to-market. As part of this transformation, the company is expanding its Artificial Intelligence capabilities to accelerate business innovation and deliver high-value solutions across multiple functions. Key Responsibilities Design, develop, and maintain Retrieval-Augmented Generation (RAG) solutions, including vector databases, embeddings, retrieval mechanisms, and LLM integration. Develop and deploy Generative AI solutions leveraging Large Language Models (LLMs) and APIs. Integrate AI capabilities into existing Robotic Process Automation (RPA) workflows to improve business process efficiency. Assess, evaluate, and recommend AI frameworks, platforms, and technologies. Build Proofs of Concept (PoCs) and lead the industrialization of successful initiatives into production environments. Ensure AI solutions are scalable, observable, secure, and compliant with data privacy, security, and regulatory requirements. Monitor, evaluate, and optimize model performance, latency, and operational costs. Collaborate with cross-functional teams to identify and implement AI-driven solutions that create business value. Mentor and support RPA developers transitioning into AI-related roles and technologies. Qualifications Minimum of 5 years of experience in software development. Strong proficiency in Python and software engineering best practices. Proven experience developing data pipelines, APIs, and system integrations. Hands-on experience in Artificial Intelligence projects, including Generative AI, Retrieval-Augmented Generation (RAG), Natural Language Processing (NLP), or Machine Learning (ML). Solid understanding of prompt engineering techniques and LLM optimization strategies. Experience working with Agile methodologies and modern DevOps practices, including CI/CD, Git, Kubernetes, and related technologies. Strong communication skills and ability to work effectively within multicultural and hybrid teams. Professional proficiency in English (spoken and written). Nice-to-Have Experience training, fine-tuning, or adapting smaller language models. Knowledge of Agentic AI architectures and frameworks. Familiarity with cloud-based AI services and MLOps practices. Experience with vector databases such as Pinecone, Weaviate, Milvus, or similar technologies. Soft Skills Organized, detail-oriented, and process-driven mindset. Excellent communication skills, with the ability to clearly present technical concepts and project updates to both technical and non-technical stakeholders. Team-oriented professional with the ability to work effectively across diverse teams. Client-focused approach with a commitment to delivering high-quality solutions. High level of motivation, accountability, and professional integrity. Additional Information Hybrid position - Lisbon.

Responsibilities

Design and deploy Generative AI and RAG solutions to enhance business processes and operational efficiency. Collaborate with cross-functional teams to build PoCs and industrialize AI capabilities within a financial institution.