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Applied AI Engineer

May 29, 2026

<h1>Job Title</h1>Applied AI Engineer<h1>Job Description Summary</h1>The Applied AI Engineer is a hands-on builder who sits at the intersection of AI engineering, operational analytics, and business process expertise. This role designs, prototypes, and operationalizes AI and analytics solutions that automate work, sharpen decision-making, and measurably improve performance across the organization. Embedded directly with operational leaders, the Applied AI Engineer translates real-world business challenges into working proofs of concept — independently building end-to-end, including the data, modeling, and lightweight infrastructure needed to demonstrate value quickly. When solutions prove valuable, this role partners with the data engineering team to harden, scale, and operationalize them for production use. Reporting to the Director of Advanced Analytics & AI, this position is a critical execution role within the centralized Advanced Analytics & AI team. Success requires equal fluency in modern AI tooling (including machine learning, NLP, and generative AI), rigorous analytical thinking, and the operational context needed to ensure solutions are trusted, adopted, and continuously improved. The ideal candidate combines technical depth with the business fluency needed to work effectively across stakeholders, data, and code.<h1>Job Description</h1><h1>Applied AI Engineer</h1><h2>Role Overview</h2>The Applied AI Engineer is a hands-on builder who sits at the intersection of AI engineering, operational analytics, and business process expertise. This role designs, prototypes, and operationalizes AI and analytics solutions that automate work, sharpen decision-making, and measurably improve performance across the organization. The Applied AI Engineer embeds directly with operational leaders to translate real-world business challenges into working proofs of concept, and partners with data engineering to harden and scale the solutions that prove valuable.Reporting to the Director of Advanced Analytics & AI, this position is a critical execution role within the centralized Advanced Analytics & AI team. Success requires the ability to move quickly and independently during the prototype phase — building end-to-end without waiting for platform support — while also collaborating effectively with data engineering, operations, and business stakeholders to take proven solutions into production. Equal fluency in modern AI tooling, rigorous analytical thinking, and operational context is essential.<h2>Responsibilities</h2><ul><li>AI Solution Development – Design, build, and iterate on applied AI and machine learning solutions — including forecasting, classification, anomaly detection, NLP, and generative AI / LLM-based workflows — with a focus on solving concrete operational problems.</li><li>Rapid Prototyping & Proof of Concept – Independently build end-to-end POCs to validate AI and analytics ideas quickly — including standing up the data, modeling, and lightweight infrastructure needed to demonstrate value before committing to production investment.</li><li>Path to Production – Partner with the data engineering team to harden, scale, and operationalize solutions that prove out: integrating them into operational systems, ensuring they are reliable and observable, and supporting iteration once deployed. Data engineering owns the platform and production pipelines; this role owns the AI/analytics solution running on them.</li><li>Evaluation & Measurement – Define success metrics, design offline and online evaluations, and quantify business impact. Build the feedback loops needed to detect drift, regression, or misuse and respond to them.</li><li>Operational Analytics & Insight – Analyze operational data, workflows, and performance trends to identify where AI and automation can deliver measurable value, and to surface actionable insights that support service delivery and efficiency.</li><li>Embedded Business Partnership – Work directly with Geography or Vertical leadership and frontline operators to understand workflows, decision points, and constraints. Translate operational problems into well-scoped AI and analytics solutions — and translate technical results back into clear, actionable guidance.</li><li>Data Preparation & Feature Engineering – Prepare, clean, and structure datasets for analytics and AI workflows. Engineer features, design retrieval strategies for LLM-based systems, and partner with data engineering on upstream data quality and pipeline needs.</li><li>Building on Databricks – Develop, test, and deploy analytics and AI solutions within the Databricks Lakehouse environment provided by the data engineering team. Apply software engineering practices — version control, testing, code review, modular design — so prototypes are easy to harden and solutions are easy to maintain.</li><li>Adoption, Change & Continuous Improvement – Partner with field and operational teams to pilot, refine, and drive adoption of AI tools. Iterate based on user feedback, evaluation results, and evolving business needs so solutions deliver compounding value over time.</li><li>Responsible AI Practice – Apply practical judgment around model limitations, hallucinations, bias, privacy, and human-in-the-loop design so deployed solutions are trustworthy and appropriate for the operational context.</li></ul><h2>Basic Qualifications</h2><ul><li>Bachelor’s degree in Analytics, Data Science, Computer Science, Engineering, or a related field</li><li>4–7 years of experience in analytics, data science, or AI/ML engineering, with at least 2 years building and deploying ML or AI solutions</li><li>Strong proficiency in Python and SQL, including writing maintainable, tested code beyond exploratory notebooks</li><li>Hands-on experience building applied AI or ML solutions — e.g., predictive models, NLP, or LLM-based applications — not only conceptual familiarity</li><li>Demonstrated ability to build end-to-end proofs of concept independently, including the data wrangling, modeling, and lightweight infrastructure needed to show value quickly</li><li>Experience partnering with data engineering or platform teams to take prototypes into production</li><li>Experience working with large datasets in modern analytics platforms such as Databricks</li><li>Demonstrated ability to translate operational problems into analytical and AI approaches that deliver measurable business outcomes</li><li>Strong communication skills with non-technical stakeholders, including the ability to make AI behavior, limitations, and results understandable</li></ul><h2>Preferred Qualifications</h2><ul><li>Production experience with generative AI, LLM APIs (e.g., OpenAI, Anthropic), RAG systems, or agentic workflows</li><li>Familiarity with MLOps tooling and practices (e.g., MLflow, model registries, CI/CD for ML, monitoring/observability)</li><li>Experience designing evaluation frameworks for AI systems, including offline benchmarks and online experimentation</li><li>Experience in operational, services, or asset-heavy environments</li><li>Exposure to predictive modeling, time series analysis, or NLP in business contexts</li><li>Familiarity with Databricks Lakehouse concepts and collaborative analytics workflows</li><li>Track record of driving adoption of analytics or AI tools within business operations, including process and change-management considerations</li><li>Ability to work independently while managing multiple concurrent initiatives</li></ul> Cushman & Wakefield also provides eligible employees with an opportunity to enroll in a variety of benefit programs, generally including health, vision, and dental insurance, flexible spending accounts, health savings accounts, retirement savings plans, life, and disability insurance programs, and paid and unpaid time away from work. In addition to a comprehensive benefits package, Cushman and Wakefield provide eligible employees with competitive pay, which may vary depending on eligibility factors such as geographic location, date of hire, total hours worked, job type, business line, and applicability of collective bargaining agreements. The compensation that will be offered to the successful candidate will depend on factors such as whether the position is covered by a collective bargaining agreement, the geographic area in which the work will be performed, market pay rates in that area, and the candidate’s experience and qualifications. The company will not pay less than minimum wage for this role. The compensation for the position is: $ 85,000.00 - $100,000.00C&W Services is an Equal Opportunity employer to all protected groups, including protected veterans and individuals with disabilities. Discrimination of any type will not be tolerated. In compliance with the Americans with Disabilities Act Amendments Act (ADAAA), if you have a disability and would like to request an accommodation in order to apply for a position at C&W Services, please call the ADA line at 1-888-365-5406 or email <a href="mailto:Accommodations@cushwake.com?subject=Accommodations" target="_blank" rel="noopener noreferrer">Accommodations@cushwake.com</a>. Please refer to the job title and job location when you contact us.INCO: “C&W Services”

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Common Interview Questions And Answers

1. HOW DO YOU PLAN YOUR DAY?

This is what this question poses: When do you focus and start working seriously? What are the hours you work optimally? Are you a night owl? A morning bird? Remote teams can be made up of people working on different shifts and around the world, so you won't necessarily be stuck in the 9-5 schedule if it's not for you...

2. HOW DO YOU USE THE DIFFERENT COMMUNICATION TOOLS IN DIFFERENT SITUATIONS?

When you're working on a remote team, there's no way to chat in the hallway between meetings or catch up on the latest project during an office carpool. Therefore, virtual communication will be absolutely essential to get your work done...

3. WHAT IS "WORKING REMOTE" REALLY FOR YOU?

Many people want to work remotely because of the flexibility it allows. You can work anywhere and at any time of the day...

4. WHAT DO YOU NEED IN YOUR PHYSICAL WORKSPACE TO SUCCEED IN YOUR WORK?

With this question, companies are looking to see what equipment they may need to provide you with and to verify how aware you are of what remote working could mean for you physically and logistically...

5. HOW DO YOU PROCESS INFORMATION?

Several years ago, I was working in a team to plan a big event. My supervisor made us all work as a team before the big day. One of our activities has been to find out how each of us processes information...

6. HOW DO YOU MANAGE THE CALENDAR AND THE PROGRAM? WHICH APPLICATIONS / SYSTEM DO YOU USE?

Or you may receive even more specific questions, such as: What's on your calendar? Do you plan blocks of time to do certain types of work? Do you have an open calendar that everyone can see?...

7. HOW DO YOU ORGANIZE FILES, LINKS, AND TABS ON YOUR COMPUTER?

Just like your schedule, how you track files and other information is very important. After all, everything is digital!...

8. HOW TO PRIORITIZE WORK?

The day I watched Marie Forleo's film separating the important from the urgent, my life changed. Not all remote jobs start fast, but most of them are...

9. HOW DO YOU PREPARE FOR A MEETING AND PREPARE A MEETING? WHAT DO YOU SEE HAPPENING DURING THE MEETING?

Just as communication is essential when working remotely, so is organization. Because you won't have those opportunities in the elevator or a casual conversation in the lunchroom, you should take advantage of the little time you have in a video or phone conference...

10. HOW DO YOU USE TECHNOLOGY ON A DAILY BASIS, IN YOUR WORK AND FOR YOUR PLEASURE?

This is a great question because it shows your comfort level with technology, which is very important for a remote worker because you will be working with technology over time...