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Ai Manager Salary Jobs (NOW HIRING)

PLP Group

Applied AI Manager

Manhattan, NY · On-site

$130 - $160/hr

The Data Science & AI team is growing, and we are looking for an Applied AI Manager to lead our ... Competitive salary and performance‑based bonus. Stock option plan. Regular team events and annual ...

Sierra Nevada Corporation

$165 - $227/hr

Lead and manage a multi-disciplinary team of AI engineers and business advisors to deliver AI ... Estimated Starting Salary Range Estimated Starting Salary Range: $165,010.21 - $226,889.04.

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Leviton

AI-Driven SEO & Discoverability Lead

Melville, NY · On-site

$100 - $120/hr

Leviton is seeking an SEO / AI Manager in Melville, New York, to lead the evolution of AI-driven ... The position offers a competitive salary range of $100,000 to $120,000 per year along with ...

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Ai Manager Salary information

What is an AI manager salary?

An AI Manager's salary can vary widely depending on factors such as location, industry, company size, and the individual's experience and education. In the United States, the average annual salary for an AI Manager ranges from $130,000 to $200,000, with some earning more in major tech hubs or large organizations. Additional compensation like bonuses and stock options can also significantly increase total earnings. Salaries tend to be higher for those with advanced technical expertise and proven leadership in artificial intelligence projects.

What factors can influence salary growth for an AI manager within an organization?

Salary growth for an AI Manager is often influenced by several factors, including the complexity and impact of AI projects managed, the size and industry of the organization, and the manager’s level of experience and technical expertise. Demonstrating strong leadership, delivering successful results, and staying updated with the latest AI technologies can also contribute to advancement opportunities and higher compensation. Additionally, AI Managers who effectively collaborate across departments and mentor team members often position themselves for raises and promotions.

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

To thrive as an AI Manager, you need expertise in artificial intelligence, machine learning, data analytics, and a strong background in computer science or related fields, often supported by advanced degrees. Familiarity with machine learning frameworks (such as TensorFlow or PyTorch), cloud computing platforms, and project management tools is typically required. Excellent leadership, strategic thinking, and communication skills help you manage cross-functional teams and align AI projects with business goals. These skills are crucial for driving effective AI initiatives and ensuring successful integration of AI solutions within organizations.

What is the difference between Ai Manager Salary vs Data Scientist Salary?

AspectAi Manager SalaryData Scientist Salary
Required CredentialsTypically requires a master's or PhD in AI, computer science, or related fieldsUsually requires a master's or PhD in data science, statistics, or related areas
Work EnvironmentLeads AI projects, manages teams, collaborates with stakeholdersAnalyzes data, builds models, supports decision-making
Employer & Industry UsageUsed in tech companies, finance, healthcare, and AI-focused firmsCommon across tech, finance, healthcare, and research institutions

While both roles require advanced technical skills and similar educational backgrounds, Ai Managers focus on leading AI initiatives and managing teams, whereas Data Scientists primarily analyze data and develop models. Salary differences depend on experience, location, and industry demand.

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Ai Manager Salary jobs near you
Infographic showing various Ai Manager Salary job openings in the United States as of August 2026, with employment types broken down into 87% Full Time, 12% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

Applied AI Manager

PLP Group

Manhattan, NY • On-site

$130 - $160/hr

Other

Posted 18 days ago

Key responsibilities

  • Lead the design and delivery of complex ML and GenAI systems for production use.

  • Guide the team through the full AI lifecycle, including experimentation, deployment, and monitoring.

  • Collaborate with cross-functional teams to shape roadmaps and deliver impactful AI solutions.

Job description

Engineering/ Product/ Tech · New York, USA · Full-time

About Cardo AI

At Cardo AI, we've been on a mission since 2018 to make Private Credit and Asset-Based Finance (ABF) markets more accessible and efficient. Today, with over $40 billion in assets under technology, our platform empowers banks, trustees, and investors to accelerate growth through smarter strategies, faster transactions, and optimized investment portfolios.

Driven by a bold vision to help grow the ABF market beyond $40 trillion, we're building a future defined by speed, confidence, and innovation. By combining automated workflows, comprehensive data, and AI-driven insights, we transform complexity into opportunity, enabling our clients to unlock growth and stay ahead.

The Data Science & AI team is growing, and we are looking for an Applied AI Manager to lead our application of AI across the platform and the business. You will work on genuinely hard problems: structured finance data is complex, high‑stakes, and largely unstructured, and you will build systems that actually change how the market operates. This is not a research role — we need someone who ships.

What You Will Do

Lead the design and delivery of complex ML and GenAI systems — robust, scalable, and built for production.

Guide the team across the full AI lifecycle, from experimentation and evaluation through deployment and monitoring, with a strong focus on reproducibility and reliability.

Drive architectural decisions for data‑intensive, AI‑driven applications, making sharp trade‑offs between cutting‑edge approaches and production readiness.

Apply NLP and GenAI to extract structure from unstructured financial documents: credit agreements, indentures, and servicer reports.

Build and deploy models that operate on structured finance data, where a logic error has real financial consequences.

Mentor and grow engineers across levels, building a high‑performing team with a strong engineering culture.

Collaborate cross‑functionally with Product, Data, and Business teams to shape roadmaps and deliver real impact.

Champion AI adoption across the organization and influence company‑wide technology strategy.

What You Bring

Proven experience leading engineering teams in a fast‑paced, high‑growth environment.

Solid understanding of structured finance: loan tapes, cash flow waterfalls, ABS/CLO structures, and priority of payments.

Strong software engineering skills (Python preferred) combined with deep knowledge of AI/ML frameworks, GenAI tooling, and modern data infrastructure.

Hands‑on experience building and deploying ML/GenAI systems in production within finance, legal, or other high‑complexity, data‑heavy domains.

Ability to lead architectural discussions and technical trade‑offs without losing sight of the details.

Familiarity with cloud infrastructure (AWS preferred) and modern MLOps practices.

Commitment to people development: mentoring, performance conversations, and building high‑performing teams.

Bonus: experience with NLP on financial contracts, RAG or LLM‑based applications on structured data, large‑scale loan data pipelines, or containerization tooling (Docker, Kubernetes, Terraform).

Competitive salary and performance‑based bonus.

Stock option plan.

Regular team events and annual retreats.

Opportunities for career growth within a fast‑scaling fintech innovator.

A collaborative, innovative, and entrepreneurial culture that values creativity, initiative, and impact.

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