AI Engineer
Modicus Prime
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Raleigh-Durham-Chapel Hill Area
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Mid-Senior level
Posted April 1, 2026
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Responsibilities
Commitments
Responsibilities
- Designs and implements agentic AI systems while ensuring compliance with regulatory requirements for GxP-regulated environments.
- Collaborates closely with platform engineering and cross-functional teams to deliver production-ready AI solutions with comprehensive observability and validation.
- Design and implement LLM-based solutions with proper observability using Langfuse for monitoring and evaluation
- Develop and deploy vision models and multi-modal AI systems for pharmaceutical applications
- Write clean, maintainable Python code with type hints following engineering best practices
- Implement AI model validation protocols that meet pharmaceutical regulatory requirements (21 CFR Part 11, GxP)
- Develop production-ready models using PyTorch with attention to performance, reproducibility, and maintainability
- Create robust data processing pipelines using NumPy and related scientific computing libraries
- Integrate AI models into CI/CD pipelines with automated linting, formatting, and security requirements
- Implement comprehensive metrics and monitoring for AI model performance, drift detection, and quality assurance
- Collaborate with platform engineering teams to ensure seamless deployment across multi-cloud Kubernetes environments
- Deliver production-ready AI models that meet pharmaceutical quality and regulatory standards
- Implement comprehensive monitoring and validation frameworks that ensure model reliability
- Collaborate effectively with platform engineering to achieve seamless model deployment
- Proactively identify and address model performance issues, drift, or quality concerns Additional Information
Commitments
This role is U.S.-based, and visa sponsorship cannot be accommodated at this time.
Location: Research Triangle, NC preferred (Raleigh-Durham-Chapel Hill Area)
Job Type: Full-time with Hybrid Work Engagement
Enjoy the benefits of a flexible work schedule within a remote working environment, while also having the opportunity to connect with your colleagues through regular in-person meetings in the Research Triangle, including team luncheons.
To Apply Please submit your CV and any relevant materials to info@modicusprime.com .
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Requirements
- Design and implement LLM-based solutions with proper observability using Langfuse for monitoring and evaluation
- Develop and deploy vision models and multi-modal AI systems for pharmaceutical applications
- Write clean, maintainable Python code with type hints following engineering best practices
- Implement AI model validation protocols that meet pharmaceutical regulatory requirements (21 CFR Part 11, GxP)
- Develop production-ready models using PyTorch with attention to performance, reproducibility, and maintainability
- Create robust data processing pipelines using NumPy and related scientific computing libraries
- Integrate AI models into CI/CD pipelines with automated linting, formatting, and security requirements
- Implement comprehensive metrics and monitoring for AI model performance, drift detection, and quality assurance
- Collaborate with platform engineering teams to ensure seamless deployment across multi-cloud Kubernetes environments
- Manage project workflows and documentation using Jira and other collaboration tools Basic Qualifications Bachelor's degree in computational science, computer science, machine learning, mathematics, or equivalent combination of education and relevant professional experience.
- 3+ years of experience in AI/ML engineering, data science, or related roles
- Strong hands-on experience with large language models (LLMs) and prompt engineering
- Practical experience developing and deploying vision models or computer vision applications
- Proficiency with PyTorch for model development and training
- Strong foundation in NumPy and scientific Python ecosystem
- Experience with AI observability and monitoring tools (Langfuse strongly preferred)
- Python with type hints for production-grade code
- Understanding of CI/CD principles and automated testing for ML systems
- Familiarity with containerization and Kubernetes concepts
- Strong collaborative skills and enjoyment of cross-functional work with engineering teams Useful Experience
- Understanding of GxP regulations, 21 CFR Part 11, or pharmaceutical quality systems
- Experience with regulated industries (pharmaceutical, medical device, biotechnology)
- Background in AI validation, model documentation, and compliance frameworks
- Familiarity with model deployment on Kubernetes and cloud platforms
- Experience with experiment tracking and model versioning tools
- Knowledge of statistical validation methods and uncertainty quantification What Success Looks Like
- Deliver production-ready AI models that meet pharmaceutical quality and regulatory standards
- Implement comprehensive monitoring and validation frameworks that ensure model reliability
- Collaborate effectively with platform engineering to achieve seamless model deployment
- Maintain clear documentation and communication of AI system behavior and limitations
- Proactively identify and address model performance issues, drift, or quality concerns Additional Information
Preferred Skills
- Advanced degree (Master's or PhD) in a related field is a plus.
- Experience with AI observability and monitoring tools (Langfuse strongly preferred)
- Python with type hints for production-grade code
- Strong collaborative skills and enjoyment of cross-functional work with engineering teams Useful Experience
- Understanding of GxP regulations, 21 CFR Part 11, or pharmaceutical quality systems
- Experience with regulated industries (pharmaceutical, medical device, biotechnology)
- Background in AI validation, model documentation, and compliance frameworks
- Familiarity with model deployment on Kubernetes and cloud platforms
- Experience with experiment tracking and model versioning tools
- Knowledge of statistical validation methods and uncertainty quantification What Success Looks Like
- Deliver production-ready AI models that meet pharmaceutical quality and regulatory standards
- Implement comprehensive monitoring and validation frameworks that ensure model reliability
- Collaborate effectively with platform engineering to achieve seamless model deployment
- Maintain clear documentation and communication of AI system behavior and limitations
- Proactively identify and address model performance issues, drift, or quality concerns Additional Information
Education
- (Not required) – Manage project workflows and documentation using Jira and other collaboration tools Basic Qualifications Bachelor's degree in computational science, computer science, machine learning, mathematics, or equivalent combination of education and relevant professional experience.
- (Not required) – Advanced degree (Master's or PhD) in a related field is a plus.
About Us Modicus Prime is improving the quality of pharmaceutical drug manufacturing and saving patient lives by leveraging the power of compliant AI and advanced analytics. Modicus Prime is a Johnson & Johnson JLABS company and venture-backed by Silverton Partners along with strategic partnerships at several large corporations including Takeda Pharmaceuticals, Oak Ridge National Laboratory (DOE), eLabNext (Eppendorf), Dotmatics, and PlugandPlay. Modicus Prime has been featured in the Wall Street Journal and BioProcess International, and the CEO is co-author of the pharmaceutical industry's ISPE AI Guide (2025). We are now seeking an AI Engineer to join our company. If you are eager to impact the AI/ML integration in the pharmaceutical industry and enjoy rapidly scaling products and teams, consider applying to join our company. This role is U.S.-based, and visa sponsorship cannot be accommodated at this time. Position Overview and Key Responsibilities Responsible for developing, validating, and deploying AI/ML solutions including large language models, vision models, and multi-modal systems for pharmaceutical manufacturing applications. Designs and implements agentic AI systems while ensuring compliance with regulatory requirements for GxP-regulated environments. Collaborates closely with platform engineering and cross-functional teams to deliver production-ready AI solutions with comprehensive observability and validation. Key Qualifications
Design and implement LLM-based solutions with proper observability using Langfuse for monitoring and evaluation
Develop and deploy vision models and multi-modal AI systems for pharmaceutical applications
Write clean, maintainable Python code with type hints following engineering best practices
Implement AI model validation protocols that meet pharmaceutical regulatory requirements (21 CFR Part 11, GxP)
Develop production-ready models using PyTorch with attention to performance, reproducibility, and maintainability
Create robust data processing pipelines using NumPy and related scientific computing libraries
Integrate AI models into CI/CD pipelines with automated linting, formatting, and security requirements
Implement comprehensive metrics and monitoring for AI model performance, drift detection, and quality assurance
Collaborate with platform engineering teams to ensure seamless deployment across multi-cloud Kubernetes environments
Manage project workflows and documentation using Jira and other collaboration tools Basic Qualifications Bachelor's degree in computational science, computer science, machine learning, mathematics, or equivalent combination of education and relevant professional experience. Advanced degree (Master's or PhD) in a related field is a plus. Required Experience
3+ years of experience in AI/ML engineering, data science, or related roles
Strong hands-on experience with large language models (LLMs) and prompt engineering
Practical experience developing and deploying vision models or computer vision applications
Proficiency with PyTorch for model development and training
Strong foundation in NumPy and scientific Python ecosystem
Experience with AI observability and monitoring tools (Langfuse strongly preferred)
Python with type hints for production-grade code
Understanding of CI/CD principles and automated testing for ML systems
Familiarity with containerization and Kubernetes concepts
Strong collaborative skills and enjoyment of cross-functional work with engineering teams Useful Experience
Understanding of GxP regulations, 21 CFR Part 11, or pharmaceutical quality systems
Experience with regulated industries (pharmaceutical, medical device, biotechnology)
Background in AI validation, model documentation, and compliance frameworks
Familiarity with model deployment on Kubernetes and cloud platforms
Experience with experiment tracking and model versioning tools
Knowledge of statistical validation methods and uncertainty quantification What Success Looks Like
Deliver production-ready AI models that meet pharmaceutical quality and regulatory standards
Implement comprehensive monitoring and validation frameworks that ensure model reliability
Collaborate effectively with platform engineering to achieve seamless model deployment
Maintain clear documentation and communication of AI system behavior and limitations
Proactively identify and address model performance issues, drift, or quality concerns Additional Information
Location: Research Triangle, NC preferred (Raleigh-Durham-Chapel Hill Area)
Job Type: Full-time with Hybrid Work Engagement
Pay (with equity): Salary/equity ratio dependent on candidate preferences, skills and/or qualifications What We Offer
Enjoy the benefits of a flexible work schedule within a remote working environment, while also having the opportunity to connect with your colleagues through regular in-person meetings in the Research Triangle, including team luncheons.
The chance to lead groundbreaking AI initiatives that are transforming the pharmaceutical industry.
A supportive and collaborative team culture, with ample opportunities for professional growth and development, including conference speaking opportunities.
Comprehensive medical, dental, and vision coverage, along with a 401(k) retirement plan. Equal Opportunity Employer Statement We are an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, or protected veteran status. To Apply Please submit your CV and any relevant materials to info@modicusprime.com . We look forward to hearing from you and exploring how your ambitions and expertise can help shape the future of Modicus Prime and the pharmaceutical industry at large.
Design and implement LLM-based solutions with proper observability using Langfuse for monitoring and evaluation
Develop and deploy vision models and multi-modal AI systems for pharmaceutical applications
Write clean, maintainable Python code with type hints following engineering best practices
Implement AI model validation protocols that meet pharmaceutical regulatory requirements (21 CFR Part 11, GxP)
Develop production-ready models using PyTorch with attention to performance, reproducibility, and maintainability
Create robust data processing pipelines using NumPy and related scientific computing libraries
Integrate AI models into CI/CD pipelines with automated linting, formatting, and security requirements
Implement comprehensive metrics and monitoring for AI model performance, drift detection, and quality assurance
Collaborate with platform engineering teams to ensure seamless deployment across multi-cloud Kubernetes environments
Manage project workflows and documentation using Jira and other collaboration tools Basic Qualifications Bachelor's degree in computational science, computer science, machine learning, mathematics, or equivalent combination of education and relevant professional experience. Advanced degree (Master's or PhD) in a related field is a plus. Required Experience
3+ years of experience in AI/ML engineering, data science, or related roles
Strong hands-on experience with large language models (LLMs) and prompt engineering
Practical experience developing and deploying vision models or computer vision applications
Proficiency with PyTorch for model development and training
Strong foundation in NumPy and scientific Python ecosystem
Experience with AI observability and monitoring tools (Langfuse strongly preferred)
Python with type hints for production-grade code
Understanding of CI/CD principles and automated testing for ML systems
Familiarity with containerization and Kubernetes concepts
Strong collaborative skills and enjoyment of cross-functional work with engineering teams Useful Experience
Understanding of GxP regulations, 21 CFR Part 11, or pharmaceutical quality systems
Experience with regulated industries (pharmaceutical, medical device, biotechnology)
Background in AI validation, model documentation, and compliance frameworks
Familiarity with model deployment on Kubernetes and cloud platforms
Experience with experiment tracking and model versioning tools
Knowledge of statistical validation methods and uncertainty quantification What Success Looks Like
Deliver production-ready AI models that meet pharmaceutical quality and regulatory standards
Implement comprehensive monitoring and validation frameworks that ensure model reliability
Collaborate effectively with platform engineering to achieve seamless model deployment
Maintain clear documentation and communication of AI system behavior and limitations
Proactively identify and address model performance issues, drift, or quality concerns Additional Information
Location: Research Triangle, NC preferred (Raleigh-Durham-Chapel Hill Area)
Job Type: Full-time with Hybrid Work Engagement
Pay (with equity): Salary/equity ratio dependent on candidate preferences, skills and/or qualifications What We Offer
Enjoy the benefits of a flexible work schedule within a remote working environment, while also having the opportunity to connect with your colleagues through regular in-person meetings in the Research Triangle, including team luncheons.
The chance to lead groundbreaking AI initiatives that are transforming the pharmaceutical industry.
A supportive and collaborative team culture, with ample opportunities for professional growth and development, including conference speaking opportunities.
Comprehensive medical, dental, and vision coverage, along with a 401(k) retirement plan. Equal Opportunity Employer Statement We are an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, or protected veteran status. To Apply Please submit your CV and any relevant materials to info@modicusprime.com . We look forward to hearing from you and exploring how your ambitions and expertise can help shape the future of Modicus Prime and the pharmaceutical industry at large.