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ATS: Workday

Expert Verified

37 ATS Keywords Inside

EY AI Engineer Resume Guide (2026): ATS Keywords, Examples & Insider Tips

Jordan Reid — Former Senior Staff Technical Recruiter (Google, Amazon) who has reviewed 12,000+ engineering, product, and business resumes.

Updated November 8, 20269 min readAI + Human ResearchInsider Knowledge

37+

ATS Keywords

for this exact role

Resume Tips

insider-specific

Bullet Rewrites

before vs after

Common Mistakes

to avoid

EY's AI & Data Engineering practice operates on a global, client-engagement model where 'production' means a live, client-facing solution driving measurable business value. Their acceptance rate for IC3-IC5 AI Engineer roles is under 4%, filtered first by Workday's keyword density scoring and a recruiter's 6-second scan for demonstrable ROI. The hiring loop blends behavioral panels assessing 'Teaming' with case interviews simulating client deliverables. Your resume is not reviewed by an AI expert first; it's triaged by a Talent Acquisition Partner in Workday using a predefined scorecard for technical competency and client-readiness signals.

ATS Insider Intelligence

How Workday Actually Works

Workday at EY parses your uploaded PDF by converting it to plain text, then indexing terms against the requisition's required skills list. It does NOT read charts, text boxes, or headers/footers reliably. The system weights keywords in the most recent 3-4 years of experience 1.8x higher than older roles or a standalone 'Skills' section. Recruiters apply binary knockout filters for non-negotiables like 'Python' and 'LLM fine-tuning' before the human review. The internal recruiter scorecard in Workday tags candidates on four pillars: Technical Depth, Quantified Business Impact, Cross-Functional Collaboration, and Alignment to EY Values. Missing signals in two pillars triggers an auto-reject.

🎯 ATS Keyword Arsenal

EY • AI Engineer • Workday — Click any keyword to copy it

⚡ Technical Skills

PythonPyTorchTensorFlowLLM fine-tuningRAG (Retrieval-Augmented Generation)machine learning operations (MLOps)Azure OpenAIAzure AI StudioLangChainscikit-learnprompt engineeringmodel evaluationfeature engineeringnatural language processing (NLP)

🔧 Tools & Platforms

Microsoft Azure (AI & ML services)DatabricksMLflowGitDockerAzure DevOpsPower BISQLJIRA

🧠 Behavioral / Soft Skills

client-facing communicationrequirements translationcross-functional teamingstakeholder presentationagile deliveryknowledge sharingbusiness outcome articulation

🏢 Domain Expertise

GDPR compliancemodel risk managementresponsible AIproof of concept (PoC) to productionclient workshop facilitationuse case prioritizationtotal cost of ownership (TCO) analysis

See how many you're already using 👇

Applying without mapping your resume to EY's specific Workday keyword rubric is like sending a blank application. A 5-minute scan for the 20 critical terms listed above can prevent your resume from being auto-filtered before a human ever sees it.

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Paste your resume bullets below to see how many of EY's 37 target ATS keywords and impact metrics you match right now.

100% client-side instant check · Zero signup requiredChecks 37 EY keywords + XYZ metric density

Expert Resume Tips for EY

Lead every bullet with a client or business problem, not a technical task.

EY consultants sell impact. Instead of 'Built a model to classify documents,' write 'Addressed a client's $2M manual document review cost by developing a fine-tuned BERT model that automated 85% of classification, deployed via Azure Container Instances.' This directly answers the recruiter's scorecard item: 'Demonstrates understanding of business context.'

Why this matters at EY

Hiring managers need candidates who can justify AI work to non-technical clients. This framing proves you translate tech into value, a core EY promotion signal.

Name-drop Microsoft Azure AI services; AWS or GCP experience is secondary.

EY's global alliance with Microsoft makes Azure the primary cloud for AI delivery. Explicitly list Azure OpenAI, Azure Machine Learning, Azure AI Search, and Azure Databricks. If you have AWS SageMaker, still include it, but prioritize Azure keywords in your top 3 experience bullets.

Why this matters at EY

Workday keyword scoring for this requisition heavily favors Azure terms. Recruiters are instructed to prioritize candidates with proven Azure AI project experience for client readiness.

Include a 'Project Overview' or 'Select Engagements' section, not just job titles.

After your role descriptions, add a section titled 'AI Project Engagements.' List 2-3 projects with this format: '[Client Industry – e.g., Financial Services]: Built a RAG pipeline using LangChain and Azure AI Search to power a regulatory Q&A chatbot, reducing compliance team query resolution time by 70%.'

Why this matters at EY

This mimics EY's internal case study format and shows you can structure client work, a prerequisite for the case interview. It also packs domain keywords Workday might miss in standard bullets.

Quantify everything in terms of efficiency gain, cost reduction, or risk mitigated.

Never say 'improved model accuracy.' Instead, write 'Increased fraud detection model precision by 22%, preventing an estimated $1.5M in monthly chargeback risk for a retail banking client.' Use percentages, dollar figures, hours saved, or risk exposure reduction.

Why this matters at EY

EY's performance reviews are based on value creation. Recruiters scan for numbers that prove economic impact, separating consultants from pure researchers.

Prominently feature 'Responsible AI' or 'Model Risk Management' as a skill.

In your skills list or a bullet, explicitly mention experience with model fairness assessment, explainability tools (SHAP, LIME), audit trails, or governance frameworks. For a domain-specific section, include 'GDPR compliance' or 'model risk management.'

Why this matters at EY

EY's brand is built on trust and integrity. Demonstrating practical knowledge of AI ethics and compliance directly addresses a key hiring committee concern for client-facing work.

Before vs After: Real Bullet Rewrites

These are the exact bullets that get filtered vs. the ones that get through Workday and land interviews.

Gets Rejected

"Responsible for developing machine learning models for client data."

Gets Noticed ✓

"For a pharmaceutical client, fine-tuned a PyTorch-based vision transformer on Azure ML to automate adverse event detection in clinical trial imagery, accelerating data review cycles by 40% and reducing manual oversight costs by 300 analyst-hours per trial."

Why it works: This names the client domain, specific tech stack (PyTorch, Azure ML), and quantifies impact in both efficiency (%) and cost (hours), hitting multiple Workday scorecard tags simultaneously.

Gets Rejected

"Used Python and LangChain to work with LLMs."

Gets Noticed ✓

"Designed and deployed a secure, internal RAG system using LangChain, Azure OpenAI GPT-4, and Azure AI Search, enabling 500+ audit professionals to query firm-wide guidance, cutting average research time from 2 hours to 15 minutes per query."

Why it works: It specifies the architecture (RAG), the exact Azure services, scales the user base (500+), and provides a stark time-reduction metric, demonstrating scalable product thinking EY values.

Gets Rejected

"Collaborated with team members to deploy models."

Gets Noticed ✓

"Teamed with data engineers and UX designers to containerize a sentiment analysis pipeline using Docker and Azure Kubernetes Service, achieving 99.5% uptime over 6 months and supporting a client's real-time brand monitoring dashboard used by 200+ marketing users."

Why it works: The verb 'Teamed' directly echoes EY's core value, lists concrete collaborators and tools, and provides production metrics (uptime, users) that signal successful client delivery.

Gets Rejected

"Built predictive models for sales forecasting."

Gets Noticed ✓

"Led the development of an ensemble model (XGBoost, Prophet) for a manufacturing client's demand forecasting, integrating SAP data via Databricks, improving forecast accuracy by 18% and optimizing inventory levels, resulting in a $2.7M reduction in carrying costs."

Why it works: It names the models, the data source (SAP), the platform (Databricks), and converts accuracy gains into a hard dollar figure, which is the ultimate language of EY's partnership.

⚡ Insider Counter-Intuition

The most counter-intuitive rule: For an EY AI Engineer resume, demonstrating how you *constrained* or *simplified* a solution is more powerful than boasting about complexity. Hiring managers seek candidates who prioritize 'fit-for-purpose,' cost-effective, and maintainable solutions for clients, not the most novel architecture. A bullet about choosing a simpler logistic regression over a deep learning model because it saved 80% in deployment costs and met the SLA shows mature, client-centric judgment—the exact trait that separates an EY consultant from a pure technologist.

Mistakes That Get AI Engineers Rejected at EY

❌ Listing only academic research or Kaggle projects without client or business context.

What happens

Workday flags 'low business impact' and the recruiter concludes you lack consulting readiness. Your application is deprioritized for candidates with industry delivery experience.

✓ The Fix

Reframe every project. If you improved a model on a public dataset, calculate the hypothetical business value: 'Technique X, applicable to retail inventory prediction, improved MAPE by 15%, which typically translates to a 5-10% reduction in stockout costs.'

❌ Burying 'Azure' experience in a long list of cloud platforms.

What happens

The Workday keyword scorer may not meet the threshold for 'Azure' if it's mentioned only once. The recruiter may assume your primary experience is elsewhere.

✓ The Fix

Mention Azure and key services (Azure OpenAI, Azure ML) in at least two role descriptions and the skills section. Use it as the primary cloud example in your strongest bullet.

❌ Using overly complex, research-paper jargon without clear explanations.

What happens

The first-line recruiter, who may not have a deep AI background, cannot map your skills to the client project needs on their scorecard. They will pass for a more clearly articulated resume.

✓ The Fix

Follow the formula: 'Business Problem -> Technical Approach (name tools) -> Quantified Outcome.' Replace 'implemented a novel attention mechanism' with 'improved document comprehension accuracy by 11% for a legal tech client using a customized transformer architecture.'

❌ Omitting any mention of data governance, security, or compliance.

What happens

In the hiring committee review, this raises a red flag about your suitability for regulated client environments (financial services, healthcare). Your resume may be flagged as 'lacking risk awareness.'

✓ The Fix

Add a bullet or line in your skills: 'Experience developing AI solutions with consideration for data privacy (GDPR), model explainability, and audit requirements.' Name a specific framework or tool if possible.

FAQ: AI Engineer at EY

Does EY's Workday ATS reject resumes based on formatting?

Yes, but not for aesthetics. Workday fails to parse text inside headers, footers, text boxes, or multi-column layouts, turning that content invisible. Simple, single-column formats with standard section headers ('Experience', 'Skills') ensure 100% parsing. Fancy templates cause keyword loss and auto-reject.

Should I get an Azure AI certification before applying to EY as an AI Engineer?

It is a significant positive signal but not a strict knockout filter. Listing 'Microsoft Azure AI Engineer Associate (or similar)' in your certifications section triggers a high-confidence tag in the recruiter's Workday dashboard, often fast-tracking the screen. It proves platform familiarity EY bills to clients.

How much experience is needed for the 'Senior AI Engineer' (IC4/IC5) level at EY?

EY's IC4 (Senior) typically requires 4-6 years with proven experience leading the technical delivery of at least 2-3 client AI projects end-to-end. IC5 (Manager) requires 6-8+ years and demonstrable experience managing project teams, client relationships, and budgets. Your resume must show leadership ('Led a team of 3 data scientists...') and business development ('Identified a $500K upsell opportunity...').

Is open-source contribution or published research valued for EY AI roles?

Valued as a differentiating 'technical excellence' signal, but secondary to client delivery experience. If included, explicitly link it to applied use cases. For example: 'Contributed to the Scikit-learn library (optimized Classifier X); applied this enhancement to improve a client model's inference speed by 30%.' This shows you bridge innovation to practice.

How does EY view candidates from non-consulting backgrounds (e.g., tech industry)?

They are sought after for technical depth but must proactively demonstrate 'client-readiness.' Your resume must translate your in-product work into a consulting narrative. Instead of 'Shipped a recommendation feature,' write 'Solved a user retention problem for the product, analogous to a client's customer churn challenge, using A/B testing of ML models that increased engagement by 15%.' This reframing is critical.