Applied AI Engineer

Job Title

Applied AI Engineer

Job Description Summary

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.

Job Description

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.

• 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.
• 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.
• 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.
• 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.
• 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.
• 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.
• 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.
• 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.
• 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.
• 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.

• Bachelors degree in Analytics Data Science Computer Science Engineering or a related field
• 47 years of experience in analytics data science or AI/ML engineering with at least 2 years building and deploying ML or AI solutions
• Strong proficiency in Python and SQL including writing maintainable tested code beyond exploratory notebooks
• Hands-on experience building applied AI or ML solutions e.g. predictive models NLP or LLM-based applications not only conceptual familiarity
• Demonstrated ability to build end-to-end proofs of concept independently including the data wrangling modeling and lightweight infrastructure needed to show value quickly
• Experience partnering with data engineering or platform teams to take prototypes into production
• Experience working with large datasets in modern analytics platforms such as Databricks
• Demonstrated ability to translate operational problems into analytical and AI approaches that deliver measurable business outcomes
• Strong communication skills with non-technical stakeholders including the ability to make AI behavior limitations and results understandable

• Production experience with generative AI LLM APIs (e.g. OpenAI Anthropic) RAG systems or agentic workflows
• Familiarity with MLOps tooling and practices (e.g. MLflow model registries CI/CD for ML monitoring/observability)
• Experience designing evaluation frameworks for AI systems including offline benchmarks and online experimentation
• Experience in operational services or asset-heavy environments
• Exposure to predictive modeling time series analysis or NLP in business contexts
• Familiarity with Databricks Lakehouse concepts and collaborative analytics workflows
• Track record of driving adoption of analytics or AI tools within business operations including process and change-management considerations
• Ability to work independently while managing multiple concurrent initiatives

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 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 candidates experience and qualifications.

The company will not pay less than minimum wage for this role.

The compensation for the position is: $ 85000.00 - $100000.00

C&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- or email. Please refer to the job title and job location when you contact us.

INCO: C&W Services