Senior AI Data Engineer

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.