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Applied Ai Engineer Jobs (NOW HIRING)

Job Title Applied AI Engineer 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 ...

Job Title Applied AI Engineer 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 ...

Job Title Applied AI Engineer 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 ...

Job Title Applied AI Engineer 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 ...

Lead Applied AI Engineer II

Arlington, VA · On-site

$117K - $155K/yr

Share this job: Share: Share Lead Applied AI Engineer II with Facebook Share Lead Applied AI Engineer II with LinkedIn Share Lead Applied AI Engineer II with Twitter Caution against fraudulent job ...

Applied AI Engineer (React + TypeScript + AI) - Phoenix, AZ Location: Phoenix, AZ Duration: Long-Term Contract Employment Type: W2 Only American Express is looking for a Hands-on Architect / Applied ...

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Job Title Applied AI Engineer 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 ...

Job Title Applied AI Engineer 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 ...

Senior Applied AI Engineer

$107K - $146K/yr

Senior Applied AI Engineer Location: Worldwide (Remote/Hybrid) Reports to: Staff Applied AI Engineer Senior Applied AI Engineer About CINC Systems CINC Systems is the largest provider of accounting ...

The Applied AI Engineer will work closely with customer executives and technical teams to design, build, and deliver impactful AI systems that generate significant business value. Responsibilities ...

Join to apply for the Applied AI Engineer role at Zania Base pay range $180,000.00/yr - $250,000.00/yr Why Zania Every enterprise spends millions of dollars on Governance, Risk, and Compliance (GRC)

Applied AI Engineer

San Francisco, CA · On-site

$179K - $240K/yr

Applied AI Engineer Everyone's talking about AI. But here's the truth: ChatGPT can't send your emails. It can't book your flights. It can't even order you lunch. Why? Because AI is trapped in a chat ...

Applied AI Engineer

New York, NY · On-site

$180K - $225K/yr

We are an applied AI lab building end-to-end software agents. We're the makers of Devin, the first AI software engineer, and Windsurf, the AI-native IDE. Together, they represent our vision for ...

Senior Applied AI Engineer

$107K - $146K/yr

Senior Applied AI Engineer Location: Worldwide (Remote/Hybrid) Reports to: Staff Applied AI Engineer Senior Applied AI Engineer About CINC Systems CINC Systems is the largest provider of accounting ...

Applied AI Engineer

New York, NY · On-site

$130K - $240K/yr

As an Applied AI Engineer, you own the technical delivery of real deployments end to end. You design the agents, build them, and are on the hook for whether they work in the field. The team is small ...

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Applied Ai Engineer information

What is the salary of applied AI engineer?

The salary of an applied AI engineer typically ranges from $80,000 to $150,000 annually, depending on experience, location, and industry. Senior roles or those requiring specialized skills in machine learning, deep learning, or specific tools may offer higher compensation.

What engineers make $500,000?

Senior engineers in specialized fields such as software engineering, data engineering, or AI engineering can earn $500,000 or more annually, especially with extensive experience, advanced skills, and in high-demand industries. Compensation often includes base salary, bonuses, and stock options, particularly at large tech companies or startups with significant funding.

What are the key skills and qualifications needed to thrive as an Applied AI Engineer, and why are they important?

To thrive as an Applied AI Engineer, you need strong proficiency in programming (especially Python), machine learning algorithms, statistics, and a relevant degree in computer science or a related field. Familiarity with frameworks like TensorFlow or PyTorch, experience with cloud platforms (such as AWS or Azure), and knowledge of data management tools are typically required. Excellent problem-solving, communication, and teamwork skills help you translate complex models into real-world solutions and collaborate across disciplines. These competencies ensure you can effectively develop, deploy, and maintain AI systems that drive business value.

What does an applied AI engineer do?

An applied AI engineer develops and implements artificial intelligence models and algorithms to solve real-world problems. They work with data, machine learning frameworks, and programming languages like Python or TensorFlow to create practical AI solutions for businesses or products.

What is the difference between Applied Ai Engineer vs Data Scientist?

AspectApplied Ai EngineerData Scientist
Required CredentialsBachelor's or Master's in CS, AI, or related fields; experience with AI frameworksBachelor's or Master's in CS, Statistics, or related fields; strong analytical skills
Work EnvironmentDevelops and deploys AI models in production environmentsAnalyzes data to extract insights and build predictive models
Industry UsageUsed in tech, healthcare, finance for deploying AI solutionsUsed across industries for data analysis and modeling

Applied Ai Engineers focus on implementing and deploying AI models in real-world applications, while Data Scientists primarily analyze data to generate insights and build predictive models. Both roles require similar educational backgrounds but differ in their core responsibilities and work environments.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as senior AI engineer, research scientist, or executive roles, which offer compensation including salary, bonuses, and stock options that total around this amount. These roles often require advanced skills in machine learning, deep learning, and experience with tools like TensorFlow or PyTorch, along with a strong track record of innovation and leadership in AI projects.

What are some common challenges Applied AI Engineers face when deploying AI models into production environments?

Applied AI Engineers often encounter challenges such as ensuring models perform consistently on real-world data, optimizing models for speed and scalability, and integrating AI solutions with existing systems. Managing data privacy, monitoring for model drift, and maintaining robust documentation are also key concerns. Collaboration with DevOps, data engineering, and product teams is essential to address these challenges effectively and deliver reliable AI-driven solutions.
More about Applied Ai Engineer jobs
What cities are hiring for Applied Ai Engineer jobs? Cities with the most Applied Ai Engineer job openings:
What states have the most Applied Ai Engineer jobs? States with the most job openings for Applied Ai Engineer jobs include:
Infographic showing various Applied Ai Engineer job openings in the United States as of July 2026, with employment types broken down into 87% Full Time, and 13% Contract. Highlights an 87% In-person, and 13% Remote job distribution.
Applied AI Engineer

Applied AI Engineer

Cushman & Wakefield

Cincinnati, OH • On-site, Remote

Full-time

Medical, Dental, Vision, Life, Retirement

Posted 11 days ago


Cushman & Wakefield rating

7.5

Company rating: 7.5 out of 10

Based on 153 frontline employees who took The Breakroom Quiz

76th of 160 rated real estate companies


Job description

Job TitleApplied AI EngineerJob Description SummaryThe 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 DescriptionApplied AI EngineerRole Overview

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.

Responsibilities
  • 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.
Basic Qualifications
  • Bachelor's degree in Analytics, Data Science, Computer Science, Engineering, or a related field
  • 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
  • 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
Preferred Qualifications
  • 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 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 - $100,000.00

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 1-888-365-5406 or emailAccommodations@cushwake.com. Please refer to the job title and job location when you contact us.

INCO: "C&W Services"

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