AI Data Engineer – Manager

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Company Overview
A global professional services organization is seeking an AI Data Engineer – Manager to lead advanced AI and data engineering initiatives. The organization combines technical innovation, consulting expertise, and human-centered design to deliver AI/ML and GenAI solutions that transform client operations. Their team focuses on creating scalable, secure, and ethical AI architectures, helping clients leverage large language models and machine learning to solve complex business challenges.

Position Summary
The AI Data Engineer – Manager will lead data architecture and engineering delivery for AI/ML/GenAI solutions, ensuring data is trusted, secure, and scalable from ingestion to consumption. This role blends hands-on technical leadership with team and delivery management, working with cross-functional teams to translate use cases into production-ready pipelines while maintaining strong data governance and operational standards.

Work You’ll Do

• Lead design and operationalization of modern data platforms to support LLM-powered applications (e.g., Claude, GPT/Codex, Gemini) including RAG, embeddings, vector search, and governed access to structured and unstructured data
• Manage day-to-day delivery with onshore/offshore teams, collaborating with data science, ML engineering, and product stakeholders
• Define AI/ML/GenAI technical direction, aligning with strategic goals and digital transformation initiatives
• Design end-to-end AI architectures, integrating cloud and on-premises systems
• Select and implement appropriate technologies for MLOps and LLMOps
• Conduct research to develop scalable AI/ML solutions, making trade-offs based on quality, scalability, performance, and cost
• Collaborate with stakeholders to align technical implementations with business requirements
• Serve as a technical advisor on AI trends, business impact, and implementation best practices
• Execute AI-powered applications using agile methodology and drive continuous improvement
• Audit AI tools, models, and engineering practices for operational excellence
• Work with security and risk teams to ensure ethical AI implementation and compliance
• Assist AI product managers and business stakeholders in understanding AI potential and limitations
• Build tools for data ingestion, feature engineering, and distributed data processing, ensuring security, reliability, and scalability

Required Qualifications

• Bachelor’s degree in Computer Science, Data Science, Statistics, Information Systems, or related field
• 6+ years consulting experience leading delivery teams, including onshore/offshore
• 6+ years experience gathering non-functional requirements and defining architecture frameworks
• 5+ years experience in AI environments and translating requirements into client-ready design documents
• 5+ years experience in software application architecture, analysis, and full system development lifecycle
• Ability to travel 0–25% depending on clients and projects
• Limited immigration sponsorship may be available

Preferred Qualifications

• Advanced degrees (Masters or PhD) preferred
• Certifications in AI/ML and Cloud platforms (AWS, Google Cloud, Azure)
• 5+ years experience in Data Science, Statistics, Machine Learning, and Generative AI/LLMs
• Experience delivering and productionizing machine learning models, NLP, and feature engineering
• 5+ years implementing cloud-based AI/ML workloads on AWS, Azure, or Microsoft platforms

Disclaimer
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1. No Endorsement: Job ads on SpringCube do not imply endorsement of their authenticity or quality.
2. No Client Relationship: This company is not a client of SpringCube unless stated.
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