EY-GDS Consulting-AI and DATA-AI Architect-Senior Manager
About the job
- Extensive pre-sales and consultative experience connecting AI capabilities to measurable business impact.
- At least 16 years of professional experience, including 5–8 years architecting and deploying enterprise-scale AI, machine learning, generative AI, and agentic AI solutions.
- Experience working with and managing global stakeholders.
- Experience delivering significant business outcomes.
- Strong RFP and RFI leadership experience, including solution shaping, writing technical sections, and conducting client-facing architecture and value engineering workshops.
- Deep expertise designing AI solutions using microservices and cloud-native architectures, including agentic AI, AI-ready data, and enterprise-scale large language model solution patterns such as retrieval-augmented generation, agents, and orchestration.
- A Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related technical field.
- Proven experience defining MLOps, LLMOps, and AgentOps architectures, including model lifecycle automation, observability, governance, and responsible AI.
- Hands-on experience deploying AI and machine learning solutions on Azure, AWS, and/or Google Cloud Platform, including platform-native services.
- Strong experience using and orchestrating large language models across cloud platforms, including OpenAI, Azure OpenAI, Bedrock, Vertex AI, Gemini AI, vector databases, and agent frameworks.
- Solid background in data modeling, SQL, and modern data architectures including Databricks, Snowflake, and Synapse.
- Strong foundational understanding of machine learning, deep learning, natural language processing, and generative AI.
- Advanced programming skills in Python, with optional PySpark, for prototyping, validation, and reference implementations.
- Experience integrating enterprise-grade security, identity, and authentication into AI, machine learning, and large-language-model applications.
- Proven expertise deploying AI and machine learning workloads on Kubernetes, Web Apps, Databricks, or similar cloud-native platforms.
- Strong working knowledge of MLOps, LLMOps, and AgentOps toolchains, including Git, MLflow, feature stores, continuous integration and continuous delivery, batch inference, and real-time endpoints.
- Familiarity with Azure DevOps, GitHub Actions, Jenkins, Terraform, AWS CloudFormation, and related DevOps tooling.
- Working knowledge of responsible AI principles, governance, model risk management, and compliance.
- Demonstrated experience delivering enterprise-grade, production-ready architectures and guiding delivery teams through implementation.
- Strong understanding of data strategy, cloud-native engineering, analytics modernization, and platform-driven transformation.
- Partner with C-suite and senior business leaders to understand strategic priorities and identify AI-led transformation opportunities that deliver business value.
- Shape, articulate, build future architectures, and present value propositions, solution narratives, and business cases for AI, generative AI, and agentic AI engagements.
- Drive account teams in pursuit cycles by contributing to RFP responses, solution design, storyline decks, and client presentations.
- Lead client discovery and ideation workshops to define AI use cases, roadmaps, and return-on-investment frameworks.
- Drive consultative selling by helping clients identify where AI can impact operations, customer experience, finance, and industry-specific value chains.
- Architect end-to-end AI, generative AI, and agentic AI solutions across Azure, AWS, and Google Cloud Platform.
- Leverage AI platforms including OpenAI, Azure OpenAI, Hugging Face, LangChain, Pinecone, ChromaDB, and agent orchestration frameworks.
- Design architecture patterns for enterprise AI systems, including retrieval-augmented generation, autonomous agent workflows, LLMOps, and scalable cloud-native deployments.
- Work with data engineering and data science teams to define data models, pipelines, and machine learning development workflows using Databricks, Synapse, Snowflake, Spark, Kubernetes, and Docker.
- Oversee delivery of AI and generative AI projects to ensure architecture integrity, engineering quality, and alignment with business value commitments.
- Act as the technical escalation point during delivery, guiding solution teams and ensuring adherence to best practices.
- Review detailed solution designs, code, and architectural artifacts to maintain technical rigor.
- Mentor and coach architects, AI engineers, and delivery teams on solution design, coding standards, and engineering excellence.
- Drive development of points of view, accelerators, prototypes, and demos using Azure AI, OpenAI, NVIDIA AI, and related technologies.
- Create industry-specific and horizontal reference architectures, reusable assets, and solution frameworks.
- Represent the practice in client discussions, internal leadership forums, and external industry events focused on AI strategy and innovation.
- Lead by example with hands-on prototyping when required and write and review high-quality, testable code.
- Guide teams in adopting MLOps, LLMOps, DevOps, observability, and secure deployment practices.
- Project and client management skills.
- Experience in solutioning and pre-sales engagements.
- Exposure to data mesh principles and domain-oriented data product design.
- Familiarity with data fabric architectures and multi-cloud data strategies.
- Familiarity with real-time analytics.
About the company
EY (Ernst & Young) provides professional services at a global scale, offering consulting, assurance, tax, and transaction advisory services. It serves clients across industries such as technology, media, real estate, hospitality, and construction. Instead of selling a single product, EY works with clients through tailored engagements where cross-disciplinary teams analyze challenges, design strategies, perform audits, help with tax planning, and assist with mergers or divestitures. What sets EY apart is its worldwide reach and integrated service model, industry-specific expertise, and focus on responsible business practices like sustainability, cybersecurity, and workforce flexibility. EY’s goal is to help organizations improve performance, manage risk, and achieve sustainable growth while building a better working world.
Company Size
5,001-10,000
Company Stage
N/A
Total Funding
N/A
Headquarters
Boston, Massachusetts
Founded
1991
Get referred to Ernst & Young
See people who can refer or advise you
Simplify's Take
What believers are saying
- EY.ai Agentic for Sales launched March 2, 2026 with Snowflake and Canva.
- EY uses client-zero deployments, scaling Copilot across 400,000 people by May 2026.
- EY’s 2026 AI assurance push monetizes client demand for governance, controls, and risk reviews.
What critics are saying
- Sabah filed RM2.4 billion audit-negligence claims against EY on July 30, 2026.
- EY set aside £188 million in March 2026 after NMC, Shell, and Made.com scrutiny.
- Repeated audit failures can destroy trust, trigger client defections, and shrink the franchise permanently.
What makes Ernst & Young unique
- EY Canvas processes 1.4 trillion journal-entry lines across 160,000 global audits.
- EY-Microsoft invested US$1b+ in May 2026 to industrialize enterprise AI delivery.
- EY launched agentic audit AI on April 7, 2026, spanning Assurance and AI assurance.
Help us improve and share your feedback! Did you find this helpful?
Benefits
Professional Development Budget
Flexible Work Hours
Remote Work Options
Company News
EY added nearly 10,000 staff globally in its 2026 financial year as AI-related revenue surged almost 50%. The Big Four firm's workforce reached 415,000, with most growth concentrated in global delivery services and offshoring centres. The Americas division saw headcount decrease by roughly 4,500, or 5%. Overall global revenue rose 4.7% to $57 billion. EY-Parthenon was the fastest-growing service line, with revenue increasing 7.4% to $6.8 billion, marking a turnaround after two years of minimal growth. Tax revenue rose 6% to $13.8 billion, whilst consulting grew 4.4% to $17.4 billion. The results reflect EY's "All-In" strategy under global chair Janet Truncale, with billions invested in transforming operations and AI services.
An Ernst & Young study found US oil and gas producers reached record production in 2025 while becoming more selective with investments. The analysis of 30 major exploration and production companies, representing 43% of US oil and gas output, showed oil production hit a study-period high, yet reserve additions from extensions and discoveries declined 11% year over year and failed to fully replace production volumes for the first time since 2021. Total capital expenditures fell 49% year over year, whilst M&A spending declined 70%. Exploration spending dropped 11% to $4.8 billion, representing only 3% of total capital expenditures. Natural gas showed stronger fundamentals, with production rising 18%, reserves increasing 14%, and discoveries up 21%.
Ernst & Young's US division is allocating $100 million this fiscal year to bonus payments rewarding employees who demonstrate adaptability, innovation, and judgement. Individual spot awards reach $500, whilst employees or teams making significant contributions can receive between $10,000 and $25,000, five times the previous programme's ceiling. The initiative also covers AI experimentation. "What we recognise signals what we value," said Ginnie Carlier, chief talent and culture officer for EY Americas. The bonuses form part of a broader strategy to reshape employee development across all career levels. Other professional services firms are pursuing similar approaches. KPMG restructured its audit internship this summer to emphasise critical thinking, whilst PwC US introduced training combining AI proficiency with human qualities like empathy. EY reported AI-related revenue grew 30% year-over-year in 2025.
EY-Parthenon has acquired SparkOptimus, a Dutch digital strategy consultancy founded in 2010. The Amsterdam-based firm employs around 50 consultants and specialises in AI transformation, digital business model redesign and technology-driven transformation. SparkOptimus founders Alexandra Jankovich and Tom Voskes, both former McKinsey consultants, said joining EY-Parthenon will create significant value for clients and staff whilst providing access to broader capabilities. The acquisition marks EY-Parthenon's first European deal since 2021. EY-Parthenon, established in 2014, is EY's strategy consulting and transactions advisory business with around 25,000 professionals globally. Mark Reich, Partner at EY-Parthenon Netherlands, said SparkOptimus' expertise will complement existing capabilities in the Dutch market. The deal closes on 1 September 2026. Financial terms were not disclosed.
The UK Government has awarded a contract worth up to £456 million to KPMG and EY to train civil servants, the Financial Times reported, citing government procurement tracker Tussell. Under the arrangement, the firms will train officials across various skills areas, including AI, between 2026 and 2028. KPMG's share is capped at £319 million, representing almost a quarter of its total UK advisory net sales from last year. EY's portion is worth £137 million, equivalent to around 13% of its UK consulting revenue. The deal is the largest single contract awarded to Big Four companies since Tussell started tracking records in 2012. The previous record was a £322 million deal between the Foreign Office and PricewaterhouseCoopers in 2012.