{"id":3961972,"url":"https://alion.io/job/ey-gds-consulting-ai-engineering-and-machine-learning-manager","title":"GDS Consulting_AI Engineering and Machine Learning Manager","company":{"id":2859,"name":"EY","domain":"ey.com","url":"https://alion.io/company/ey-com","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"SuccessFactors","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Taguig, Philippines"],"countries":["PH"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":8,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"Docker","optional":false},{"name":"GCP","optional":false},{"name":"Kubernetes","optional":false},{"name":"Machine Learning","optional":false},{"name":"MLFlow","optional":false},{"name":"NLP","optional":false},{"name":"OpenAI","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"SQL","optional":false},{"name":"Semantic Search","optional":true},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-11-09T12:06:52Z","employer_posted_date":"2026-11-09","last_verified_at":"2026-11-11T11:28:42Z","board_verified":true,"closed_at":null,"days_open":1,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":1},"description":"EY GDS - AI & Data\nManager - AI/ML Transformation & Delivery\nRole Overview\nEY GDS is seeking an experienced AI/ML Manager to lead enterprise AI transformation initiatives, drive innovation, and deliver scalable AI solutions that create measurable business value. This role combines AI strategy, solution architecture, delivery leadership, people management, and stakeholder engagement across Machine Learning, Generative AI, and Intelligent Automation programs.\nThe ideal candidate brings 8-11 years of experience in Data Science, Machine Learning, and AI, with deep expertise in Generative AI, LLMs, AI Agents, RAG architectures, MLOps, and Cloud AI platforms. You will be responsible for shaping AI roadmaps, leading high-performing teams, and enabling organizations to accelerate AI adoption at scale.\nKey Responsibilities\nAI Strategy & Business Transformation\nDefine and execute AI strategies aligned with business objectives and digital transformation goals.\nIdentify, prioritize, and deliver AI use cases that drive measurable business outcomes, operational efficiency, and competitive advantage.\nPartner with business leaders, clients, and stakeholders to translate strategic priorities into scalable AI solutions.\nServe as a trusted advisor on AI adoption, governance, and enterprise AI operating models.\nAI Solution Architecture & Delivery\nOwn the architecture, design, and technical direction of enterprise AI platforms and solutions.\n Lead the implementation of Machine Learning, Generative AI, AI Agents, and Retrieval-Augmented Generation (RAG) solutions.\nEstablish scalable and secure AI architectures leveraging Azure AI, OpenAI, Databricks, and modern cloud ecosystems.\nDrive delivery excellence across multiple AI engagements and programs.\nAI Engineering & MLOps\nEstablish enterprise MLOps practices covering model development, deployment, monitoring, governance, and lifecycle management.\nLead implementation of CI/CD pipelines and AI platform automation.\nDrive adoption of modern AI engineering frameworks, including MLflow, Docker, Kubernetes, and Infrastructure-as-Code practices.\nEnsure AI solutions are reliable, scalable, secure, and production-ready.\nLeadership & Talent Development\nLead, coach, and mentor teams of Data Scientists, ML Engineers, and AI Engineers across multiple engagements.\nBuild high-performing teams through technical leadership, capability development, and career coaching.\nSupport workforce planning, resource management, and competency growth initiatives.\nFoster a culture of innovation, continuous learning, and engineering excellence.\nResponsible AI & Governance\nChampion Responsible AI practices, including fairness, explainability, transparency, security, privacy, and compliance.\nEstablish governance frameworks for enterprise AI and Generative AI implementations.\nEnsure AI solutions meet regulatory, ethical, and organizational standards.\nPractice Growth & Innovation\nContribute to business development, solutioning, proposals, and AI thought leadership initiatives.\nEvaluate emerging AI technologies and drive adoption of innovative capabilities across the practice.\nSupport the growth of EY’s AI & Data capabilities through reusable assets, accelerators, and best practices.\nRequired Qualifications\nBachelor's or Master's degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, AI or a related field.\n8-11 years of experience in Artificial Intelligence, Machine Learning, Data Science, or Advanced Analytics.\nProven experience leading enterprise AI/ML programs and managing technical teams.\nStrong expertise in Python and SQL.\nHands-on experience with Machine Learning, Deep Learning, Generative AI, NLP, LLMs, AI Agents, and RAG architectures.\nExperience architecting and deploying AI solutions on Azure, AWS, or GCP.\nStrong understanding of AI platform architecture, model governance, and MLOps best practices.\nExcellent leadership, stakeholder management, consulting, and communication skills.\nDemonstrated ability to translate business challenges into AI-driven outcomes and value realization.\nPreferred Qualifications\nExperience with Azure OpenAI, Azure AI Foundry, Azure Machine Learning, Databricks, MLflow, and Spark.\nKnowledge of vector databases, semantic search, knowledge engineering, and agentic AI frameworks.\nExperience driving AI governance, model risk management, and Responsible AI initiatives.\nExperience leading global delivery teams and large-scale transformation programs.\nRelevant Microsoft Azure, Databricks, AWS, or GCP certifications.\nWhat Success Looks Like\nA successful AI/ML Manager is a business-focused AI leader who combines strategic thinking, technical depth, and people leadership to:\nDeliver enterprise-scale AI solutions that generate measurable business impact.\nBuild and lead high-performing AI teams.\nDrive AI adoption across business functions and client engagements.\nEstablish scalable AI platforms, governance, and engineering standards.\nContribute to the growth and market leadership of the AI & Data practice.\nThis role is ideal for leaders who can bridge business strategy, AI innovation, and delivery execution while developing the next generation of AI talent.","description_format":"text","description_chars":5190,"description_truncated":false,"requirements":{"experience_years_min":8,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":["Continuous 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