AI Automation Engineer Jobs
AI Automation Engineer jobs are open from entry-level to staff and principal across technology, finance, healthcare, and manufacturing, with specializations in RPA development, ML pipeline automation, and intelligent process orchestration. See the openings below and apply to the ones that match your experience.
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Posting Details
The successful candidate will teach graduate-level courses in Artificial Intelligence and Machine Learning, with a particular emphasis on applications in Biomedical Sciences, Environmental Science, and Environmental Public Health, as well as undergraduate courses as needed.
We seek an enthusiastic, innovative, and student-centered educator who is passionate about advancing AI education, mentoring students, and applying emerging technologies to real-world scientific and public health challenges.
The selected candidate will have the opportunity to contribute to the University’s new interdisciplinary Master’s program in Artificial Intelligence and Machine Learning for Biomedical and Environmental Health Systems (AIM-BEHS), helping prepare the next generation of professionals to use AI-driven approaches to address critical challenges in healthcare, biomedical research, environmental sustainability, and public health.
- A Ph.D. in Artificial Intelligence, Machine Learning, Data Science, Computer Science, Computational Science, Biomedical Sciences, Environmental Science, Environmental Health, Environmental Public Health, Engineering, or a closely related field by the start date of appointment.
- Demonstrated expertise or a strong academic or research background in AI, Machine Learning, Data Science, or computational methods, with the ability to apply these technologies to biomedical, environmental, or public health challenges.
- Demonstrated ability or strong potential to teach graduate-level courses in Artificial Intelligence, Machine Learning, and related disciplines, including interdisciplinary applications.
- Evidence of scholarly achievement, research experience, or strong potential to develop research projects and engage graduate and undergraduate students in research and applied learning.
- Ability and willingness to collaborate with faculty and researchers from diverse scientific and technical disciplines.
- Strong communication, organizational, and interpersonal skills, with a commitment to effective teaching, student mentorship, and academic excellence.
- Commitment to supporting student success, interdisciplinary education, scholarly activities, and university service.
- Teaching, research, postdoctoral, or relevant industry experience in Artificial Intelligence, Machine Learning, or Data Science.
- Experience with AI/ML tools and programming environments such as Python, R, TensorFlow, PyTorch, or related technologies.
- Experience applying AI/ML techniques to biomedical research, Bioinformatics, healthcare, environmental monitoring, environmental health, or public health data.
- Experience developing interdisciplinary research projects, mentoring students, or collaborating on externally funded research.
- Familiarity with emerging AI technologies, including deep learning, generative AI, and advanced data analytics.
- Interest in contributing to the development and growth of a new interdisciplinary graduate program.
- Curriculum vitae.
- One combined document that includes:
- Cover letter describing teaching and research interests.
- Statement of teaching philosophy.
- Statement of research interests, including plans for student involvement.
- All graduate transcripts (unofficial transcripts are acceptable for initial review).
- Names and contact information for three professional references.
- Three professional reference letters.
Equal Opportunity Statement
Supplemental Questions
Required fields are indicated with an asterisk (*).
Documents Needed To Apply
- Resume
- Cover Letter
- Transcripts
- Letter of Recommendation
- Curriculum Vitae
- Portfolio
Posting Details
The successful candidate will teach graduate-level courses in Artificial Intelligence and Machine Learning, with a particular emphasis on applications in Biomedical Sciences, Environmental Science, and Environmental Public Health, as well as undergraduate courses as needed.
We seek an enthusiastic, innovative, and student-centered educator who is passionate about advancing AI education, mentoring students, and applying emerging technologies to real-world scientific and public health challenges.
The selected candidate will have the opportunity to contribute to the University’s new interdisciplinary Master’s program in Artificial Intelligence and Machine Learning for Biomedical and Environmental Health Systems (AIM-BEHS), helping prepare the next generation of professionals to use AI-driven approaches to address critical challenges in healthcare, biomedical research, environmental sustainability, and public health.
- A Ph.D. in Artificial Intelligence, Machine Learning, Data Science, Computer Science, Computational Science, Biomedical Sciences, Environmental Science, Environmental Health, Environmental Public Health, Engineering, or a closely related field by the start date of appointment.
- Demonstrated expertise or a strong academic or research background in AI, Machine Learning, Data Science, or computational methods, with the ability to apply these technologies to biomedical, environmental, or public health challenges.
- Demonstrated ability or strong potential to teach graduate-level courses in Artificial Intelligence, Machine Learning, and related disciplines, including interdisciplinary applications.
- Evidence of scholarly achievement, research experience, or strong potential to develop research projects and engage graduate and undergraduate students in research and applied learning.
- Ability and willingness to collaborate with faculty and researchers from diverse scientific and technical disciplines.
- Strong communication, organizational, and interpersonal skills, with a commitment to effective teaching, student mentorship, and academic excellence.
- Commitment to supporting student success, interdisciplinary education, scholarly activities, and university service.
- Teaching, research, postdoctoral, or relevant industry experience in Artificial Intelligence, Machine Learning, or Data Science.
- Experience with AI/ML tools and programming environments such as Python, R, TensorFlow, PyTorch, or related technologies.
- Experience applying AI/ML techniques to biomedical research, Bioinformatics, healthcare, environmental monitoring, environmental health, or public health data.
- Experience developing interdisciplinary research projects, mentoring students, or collaborating on externally funded research.
- Familiarity with emerging AI technologies, including deep learning, generative AI, and advanced data analytics.
- Interest in contributing to the development and growth of a new interdisciplinary graduate program.
- Curriculum vitae.
- One combined document that includes:
- Cover letter describing teaching and research interests.
- Statement of teaching philosophy.
- Statement of research interests, including plans for student involvement.
- All graduate transcripts (unofficial transcripts are acceptable for initial review).
- Names and contact information for three professional references.
- Three professional reference letters.
Equal Opportunity Statement
Supplemental Questions
Required fields are indicated with an asterisk (*).
Documents Needed To Apply
- Resume
- Cover Letter
- Transcripts
- Letter of Recommendation
- Curriculum Vitae
- Portfolio
See All 675+ AI Automation Engineer Jobs
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Find AI Automation Engineer JobsAI Automation Engineer Job Market
Who's Hiring
- JPMorganChase13
- Booz Allen Hamilton12
- Johns Hopkins University Applied Physics Laboratory9
- Amazon8
- AMD7
Top Industries Hiring
- Technology & Software18
- Banking & Financial Services11
- Education10
- Healthcare & Medical Services5
- Investment & Asset Management4
What Employers Look For
The qualifications that appear most often in AI automation engineer jobs.
- Proficiency in Python for scripting, data manipulation, and automation workflow development
- Hands-on experience with RPA platforms such as UiPath, Blue Prism, or Automation Anywhere
- Experience building and maintaining ML or data pipelines using tools like Airflow, Prefect, or Kubeflow
- Familiarity with cloud platforms including AWS, Azure, or Google Cloud for deploying automated solutions
- Bachelor's degree in computer science, engineering, or a related technical field
- Experience integrating APIs and connecting disparate enterprise systems within automated workflows
Tips for Your AI Automation Engineer Job Search
Tailor your resume to automation stacks
List the specific orchestration tools, RPA platforms, and ML frameworks you've used rather than broad terms like 'automation experience.' Hiring managers scan for tool names like UiPath, Apache Airflow, and Prefect before reading anything else.
Quantify pipeline impact, not just tasks
Describe what your automation actually replaced or improved: hours saved per week, error rates reduced, or deployment frequency increased. Vague claims about 'streamlining workflows' disappear next to concrete outcomes on a resume.
Apply early to roles that fit
Migrate Mate lists ai automation engineer openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Filter openings by tech stack, not just title
Job titles for this role vary widely: AI Engineer, Process Automation Developer, Intelligent Automation Engineer. Search for the platforms and frameworks you know, not only the title, to find openings that match your actual skills.
Prepare a live demo for technical screens
Many interviews include a whiteboard or take-home where you design an automation pipeline from scratch. Practice walking through tool selection, error handling, and monitoring out loud so you can explain decisions clearly under pressure.
Negotiate scope, not just base pay
AI automation roles differ sharply in whether you own architecture decisions or execute pre-defined specs. Before accepting, clarify what systems you'll own, what tech stack is locked in, and whether greenfield projects are on the roadmap.
AI Automation Engineer Jobs: Frequently Asked Questions
Which companies are hiring the most ai automation engineers?
The most active employers for ai automation engineers right now are JPMorganChase, Booz Allen Hamilton, and Johns Hopkins University Applied Physics Laboratory, and the most openings are in California, Texas, and Virginia, based on current listings on Migrate Mate as of November 2026. Demand is concentrated in technology services, financial institutions, and large enterprise employers modernizing legacy operations.
How many ai automation engineer jobs are remote?
About 67% of ai automation engineer openings are fully remote or hybrid as of November 2026, reflecting the infrastructure-heavy nature of the work. Sub-areas focused on ML pipeline development and cloud-native automation tend to be the most remote-friendly, while roles that require on-site system integration or RPA deployment often expect some in-person presence.
How do you become an ai automation engineer?
Start by building a strong foundation in Python and at least one cloud platform, then work through hands-on projects that connect APIs, automate repetitive data workflows, and deploy a basic ML pipeline end-to-end. Certifications in RPA platforms or cloud services strengthen your resume. Contributing to open-source automation tools or publishing a portfolio project gives hiring managers something concrete to evaluate beyond your work history.
How do you get hired as an ai automation engineer with little or no experience?
Build a portfolio of automation projects you can walk through in an interview: a web scraper that feeds a database, a scheduled data pipeline, or an RPA bot that handles a repetitive task. Roles titled Junior Automation Engineer or Associate AI Engineer often accept candidates who can demonstrate practical tool fluency over years of experience. Focus applications on companies actively modernizing operations rather than those hiring only for maintenance of existing systems.
What does the ai automation engineer interview process look like?
Most processes run three to four stages: an initial recruiter screen focused on your background and tool experience, a technical screen where you walk through a past project or solve a pipeline design problem, and a final round with the engineering team that may include a live coding exercise or systems design challenge. Some employers add a take-home automation task. Expect questions about error handling, monitoring, and how you'd approach integrating a new system into an existing workflow.
Where can I find and apply to ai automation engineer jobs?
You can find and apply to ai automation engineer jobs on Migrate Mate, which lists current openings from across the United States. Search for roles that match your stack and experience level, then apply directly to each listing. The search updates regularly, so checking back frequently gives you the best chance of catching newly posted openings before they fill.
See All 675+ AI Automation Engineer Jobs
Find roles that match your experience and apply in just a few clicks.
Find AI Automation Engineer Jobs