Senior AI Data Engineer | WFH | Dayshift

Job Applicant Privacy Notice Publication Date: Jun 11, 2026 Ref. No: 547662 Location: About Atos Group Atos Group is a global leader in digital transformation with c. 56,000 employees and annual revenue of c. €7.2 billion (at the go-forward perimeter), operating in 54 countries under two brands - Atos for services and Eviden for products and systems. European number one in cybersecurity and a leader in cloud, Atos Group is committed to a secure and decarbonized future and provides tailored AI-powered, end-to-end solutions for all industries. Atos Group is the brand under which Atos SE (Societas Europaea) operates. Atos SE listed on Euronext Paris. The purpose of Atos Group is to help design the future of the information space. Its expertise and services support the development of knowledge, education and research in a multicultural approach and contribute to the development of scientific and technological excellence. Across the world, the Group enables its customers and employees, and members of societies at large to live, work and develop sustainably, in a safe and secure information space. Senior AI Data Engineer | WFH | Dayshift Role Summary: As a Senior AI Data Engineer, you will play a key role in designing and delivering intelligent data and automation solutions for enterprise clients. You will focus on architecting and developing advanced AI-driven workflows and data pipelines that integrate APIs, systems, and machine learning capabilities to optimize business processes. This role combines data engineering expertise with emerging AI integration and automation skills, supporting global operations in a managed services environment. Key Responsibilities: Design and develop end-to-end automated workflows using low-code orchestration platforms (e.g., n8n) to integrate APIs, applications, databases, and business systems into robust multi-step AI-powered processes. Implement and fine-tune AI components within workflows, including advanced LLM (Large Language Model) prompt engineering, tool integrations, memory management, retrieval-augmented generation (RAG) pipelines, and AI agent behavior tuning for accuracy, reliability, and cost efficiency. Develop and maintain reusable workflow assets (templates, modular sub-workflows, shared libraries) with version control and best practices to accelerate future use-case delivery and standardize solutions. Collaborate with cloud architects, platform engineers, security teams, and business stakeholders to translate use cases into secure, scalable solutions aligned with enterprise architecture, compliance standards, and governance policies. Monitor, operate, and continuously improve workflows in production by tracking performance metrics, debugging issues, refining logic and prompts, managing integrations, and ensuring measurable business impact (e.g., improved quality, efficiency, reduced manual effort). Work in an Agile and DevOps environment, integrating workflow automations with continuous integration/continuous deployment (CI/CD) pipelines and using IT Service Management tools (e.g., ServiceNow) to manage deployments, changes, and incidents in line with SLA-driven support processes. Required Skills & Qualifications: Bachelor’s degree in Computer Science, Software Engineering, Data Science, or a related field (or equivalent practical experience). Proven experience in data engineering, software development, or intelligent automation, including building production-grade data workflows or pipelines in an enterprise environment. Proficiency in programming and scripting with languages such as Python and/or JavaScript for custom logic development, data transformation, and workflow extensions. Strong understanding of large language model (LLM) integration and prompt engineering concepts for AI-driven solutions (structured prompts, use of memory, RAG techniques, and human-in-the-loop design). Hands-on experience with workflow automation and integration platforms (such as n8n , UiPath , or similar iPaaS tools) for orchestrating business processes across diverse systems and data sources. Solid understanding of cloud infrastructure fundamentals (preferably on AWS , Azure , or GCP ), including containerization (Docker/Kubernetes), basic networking, and secure configuration management (e.g., credentials, environment variables). Familiarity with DevOps practices and tools for CI/CD, version control (e.g., Git), and automated testing to ensure reliable deployment of data and AI solutions. Preferred Skills (Nice to Have): Relevant industry certifications (e.g., Azure Data Engineer , Google Professional Data Engineer , or AWS Certified Machine Learning Specialty ). Working knowledge of IT Service Management (ITIL) processes and experience using ITSM tools like ServiceNow or JIRA for managing workflows in a support environment. Experience with AI/ML frameworks (e.g., TensorFlow, PyTorch) or LLM orchestration and vector database tools (e.g., LangChain, Pinecone) is a plus. Familiarity with enterprise data warehousing , ETL/ELT pipelines, and data governance standards (e.g., GDPR compliance, data security best practices). Proficiency in French or other additional languages (in addition to English) is a plus. Experience Level: Senior Data Engineer (L3) – Typically 5–8 years of professional experience in data engineering, software development, and/or AI automation roles, with a strong track record of delivering enterprise-grade solutions. Certifications: Cloud Platform Certifications: AWS, Azure, or GCP certifications (e.g., Azure Data Engineer Associate , AWS Solutions Architect , Google Professional Data Engineer ) are highly valued. AI/ML Certifications: Certifications in AI/ML (e.g., Azure AI Engineer , Google ML Engineer , IBM AI Engineering ) are a strong plus. ITSM/DevOps: ITIL Foundation or related service management certifications (beneficial for roles involving managed services/AMS support). Soft Skills / Behavioral Expectations: Communication: Excellent communication skills in English (both written and verbal); able to convey complex technical concepts to non-technical stakeholders and work effectively with globally distributed teams. Problem-Solving & Learning: Strong analytical thinking and problem-solving abilities, with a proactive approach and a commitment to continuous learning of new technologies and best practices. Collaboration: Team-oriented and proactive attitude, capable of working in cross-functional and multi-cultural environments, and collaborating closely with peers, clients, and stakeholders. Professionalism: High level of accountability, attention to detail , and commitment to delivering quality results that meet or exceed business objectives. Working Conditions: Location & Team: Based in the Atos Global Delivery Center in Manila, Philippines, providing offshore support to a leading global client (hospitality sector). Hours: Full-time role; flexibility to work in shifts or align with European time zones as needed to support global operations. Support Model: May involve participation in on-call rotations for 24/7 production support and incident response as part of an Application Management Services (AMS) delivery model. Work Environment: Hybrid remote/on-site arrangement, adhering to all client security, data privacy, and compliance requirements. #LI-PH #LI-PHI #LI-PHE Here at Atos, diversity and inclusion are embedded in our DNA. Read more about our commitment to a fair work environment for all. Atos is a recognized leader in its industry across Environment, Social and Governance (ESG) criteria. Find out more on our CSR commitment. Choose your future. Choose Atos.