What Can You Do with an MS in AI? 10 Real-World Roles Hiring Now—Across Industries

Artificial intelligence is redefining work throughout the world. Healthcare, finance, manufacturing, education, and more are seeing the power of AI transform the way sectors operate.

For professionals with data, engineering, or IT experience, this shift opens unprecedented opportunities, as well as new complexity. Employers aren’t only hiring coders or data scientists. They’re seeking professionals who can build, apply, and govern AI responsibly across disciplines.

For individuals with a background in technology, an MS in AI can significantly boost their careers, providing a launchpad into new and innovative applications of artificial intelligence. The Master of Science in Artificial Intelligence (MSAI) program at Northeastern University, for example, has an interdisciplinary structure, featuring courses from the Khoury College of Computer Sciences and the College of Engineering that positions graduates to operate fluently across technical, ethical, and business contexts. Combined with Northeastern’s experiential learning model, the MSAI builds both the foundation and flexibility needed to succeed in today’s AI-driven world.

From broad opportunity to industry-specific roles

AI is now a core operational layer across nearly every industry. Whether optimizing patient outcomes, streamlining supply chains, or ensuring fair lending, today’s organizations need professionals who can connect data, models, and outcomes responsibly.

An MS in Artificial Intelligence prepares you to meet that demand by pairing technical expertise with applied context. The following sections explore five industries where AI adoption is accelerating most rapidly, highlighting 10 roles that graduates of Northeastern’s MS in AI and related programs are stepping into right now.

Healthcare: AI roles transforming patient care and clinical operations

The global healthcare AI market is projected to reach $187 billion by 2030, creating demand for professionals who can apply machine learning safely in high-stakes settings.

Some of the roles graduates from the MS in AI program could explore include:

1. Clinical AI engineer

Clinical AI engineers design and deploy models that assist in patient diagnostics, treatment recommendations, and operational efficiency. They work with datasets such as imaging scans, EHRs, and real-time monitoring data, applying supervised and unsupervised learning to detect anomalies or forecast outcomes.

Hospitals, medtech startups, and digital health platforms are actively hiring for these roles as healthcare systems adopt AI-assisted diagnostics. At Northeastern, the MS in AI program offers concentrations in computer vision and healthcare applications through cross-college collaboration. Those seeking a shorter or non-coding path can start with the AI Applications Graduate Certificate, which introduces ethical and applied uses of AI in fields like health sciences.

2. Medical imaging/computer vision specialist

These specialists build image recognition and segmentation models to assist radiologists and pathologists. With advances in convolutional neural networks (CNNs) and diffusion models, these roles routinely bridge AI research and clinical implementation.

The computer vision concentration in Northeastern’s MSAI program offers direct preparation, where students can also explore electives in the College of Engineering’s robotics and perception labs, integrating visual AI with automation systems.

Finance & insurance: AI in risk, fraud, and decision intelligence

Financial services is among the sectors increasing AI hiring, particularly for risk modeling, fraud detection, and compliance, showing that banks, insurers, and fintech firms are hiring professionals who can build, monitor, and interpret models that drive lending, fraud prevention, and risk management.

Common roles in the financial sector would be:

3. AI risk modeler/quantitative analyst

Risk modelers apply machine learning to pricing, credit risk, and investment forecasting. They build predictive systems that evaluate loan portfolios, stress-test trading strategies, or simulate macroeconomic scenarios.

Firms such as Goldman Sachs, Fidelity, and Citigroup are expanding AI-based risk teams to meet regulatory transparency standards. At Northeastern, graduates of the MS in AI program are prepared for these analytical roles through advanced math, data processing, and machine learning courses. For professionals transitioning from finance or economics, the Master of Science in Computer Science–Align program offers a bridge into technical computing skills before specializing in AI.

4. Fraud detection machine learning engineer

These engineers develop anomaly detection and behavior-based models that flag potential fraud in real time—an essential function as digital payments surge. According to IBM research, many organizations are increasing their investment in AI, with enterprises in the financial services sector among the most likely to be actively using AI. While AI adoption is outpacing AI security, with some organizations reporting breaches of AI models or applications, other IBM research highlights the use of AI for fraud detection in banking.

Those interested in this line of work can gain the skills necessary through the MS in AI program at Northeastern, as well as the  MPS in Applied AI, which can be ideal for practitioners focused on operational systems and deployment pipelines rather than theoretical model development.

Tech & SaaS: Product-facing AI engineering roles

The software industry continues to lead AI hiring, but instead of pure research, companies now recruit engineers who can deploy, monitor, and optimize AI products in production environments.

Two of the most common roles in this sector include:

5. AI product engineer (LLMs, copilots, recommenders)

These engineers integrate AI directly into user experiences, building copilots, search assistants, and personalization engines. They can translate model outputs into intuitive features that drive engagement and retention.

SaaS companies—those that are product-led—the share of job listings specifically mentioning AI has increased significantly, and companies are paying a premium for AI skills, according to Glassdoor Economic Research. Northeastern’s MS in AI program teaches the skills necessary for engineers to balance algorithmic innovation with deployment realities through its applied programming and MLOps coursework. 

Career changers with software backgrounds can pursue the AI Applications Certificate to build fluency before committing to a full master’s.

6. MLOps/platform engineer

Platform engineers ensure that AI models run efficiently and reliably at scale. They design pipelines for data ingestion, model deployment, version control, and monitoring, bridging data science and DevOps.

As organizations deploy AI enterprise-wide, demand for MLOps professionals (computer and information research scientists) is projected to grow by 20% through 2034, according to the Bureau of Labor Statistics. Students in Northeastern’s MS in AI program can take College of Engineering electives in distributed computing or Machine Learning Operations, while those who enter the MPS in Applied AI program gain the applied systems knowledge needed for these roles.

Manufacturing & robotics: AI for optimization and automation

AI is fueling the next industrial transformation, where manufacturers are projected to generate billions in productivity gains from AI adoption by 2030.

MS in AI graduates will have the chance to work as:

7. Robotics/autonomous systems engineer

These engineers design intelligent robots and self-operating machines that integrate sensors, computer vision, and control algorithms. Their work spans logistics, defense, automotive, and consumer electronics.

Robotics engineering roles are growing 9% annually as automation expands across sectors, and the MS in AI robotics concentration at Northeastern combines advanced AI with mechatronics and perception.

8. Predictive maintenance/forecasting analyst

This role focuses on using sensor data and time-series analysis to anticipate equipment failures before they occur, thus reducing downtime and operational cost.

Predictive analytics roles in manufacturing are among the top five fastest-growing AI jobs globally, and the Northeastern MS in AI program allows students to tailor electives in data analytics. Those who enroll in the MPS in Applied AI are prepared for roles closer to operational deployment.

Education, policy, and ethics: AI that builds trust

With AI permeating every sector, ethical and regulatory oversight has become a defining need. The global AI governance market is expected to reach $6 billion by 2029.

Roles that graduates could explore in this sector include:

9. Responsible AI engineer/red-teamer

Responsible AI engineers stress-test systems for bias, data leakage, and misuse before they reach the public. A “red-teamer” mostly refers to a cybersecurity professional who plays the role of an attacker to intentionally find vulnerabilities and weaknesses in an organization’s systems.

Governments and tech firms are staffing new compliance teams to meet emerging AI governance regulations. That means those who emerge from programs, such as MS in AI at Northeastern, which integrates ethics across its curriculum, with dedicated coursework in algorithmic bias and human-in-the-loop systems, emerge ready to take advantage of these new priorities.

10. AI policy & governance lead

AI policy leads set frameworks for safe, transparent, and equitable AI use, translating complex technology into accountable systems that align with law and public interest. To ensure accountable AI systems, organizations are recruiting governance leaders who set frameworks to align with evolving standards like the EU AI Act and ISO/IEC 42001. These frameworks are used to translate complex technology and policy requirements into transparent, safe, and equitable AI use.

Students interested in ethical leadership can pair the MS in AI at Northeastern with electives in law, public policy, or philosophy. The MSCS–Align pathway also supports non-CS professionals transitioning into AI governance or compliance-focused roles.

Why Northeastern’s MS in AI and AI portfolio stand out

Northeastern’s MS in Artificial Intelligence and its companion programs stand out for their emphasis on interdisciplinary fluency and industry integration, including:

• Interdisciplinary design: The MS in AI spans five concentrations across the College of Engineering and Khoury College of Computer Sciences—Machine Learning, Robotics & Agent-Based Systems, Computer Vision, Energy Systems, Continuous Process Engineering. Students gain both technical mastery and contextual understanding of how AI systems impact organizations and society
• Experiential learning: Northeastern offers graduate co-op and experiential learning options that help students apply classroom learning in industry roles; availability varies by program and campus..
• Stackable pathways: Learners can start small and build upward. The AI Applications Graduate Certificate provides a non-coding introduction to AI concepts. The MPS in Applied AI offers an applied, systems-level focus for professionals managing AI implementation. Professionals without a computer science background can begin with the MPS in Applied AI—Connect pathway, which includes preparatory coursework before entering the full Applied AI curriculum.

The MSCS–Align helps those from non-technical backgrounds transition into AI or data science with foundational computer science training.

• Responsiveness to industry change: Faculty continuously adapt curricula to emerging technologies and workforce needs. As AI evolves—from multimodal models to generative agents—the program updates electives to keep students aligned with industry practice.

Beyond the core programs, several other Northeastern master’s degrees—including Information Systems, Software Engineering Systems, Biotechnology, and Project Management—offer concentrations in AI as part of the university’s broader ecosystem.

Take the next step

Whether you’re optimizing clinical workflows, automating financial decisions, or governing AI responsibly, an MS in Artificial Intelligence from Northeastern University equips you to lead the transformation rather than react to it.

Looking for a better understanding of timelines, pathways, and career outcomes? Explore all of Northeastern’s AI portfolio today and see how the experiential, human-centered approach can fit into your life—and your future in AI.