AI Engineer – Clinical AI Platforms (Remote-US)

AI Engineer – Clinical AI Platforms (Remote-US)

We are looking to hire a candidate with the skills sets mentioned and experience for one of our clients within the pharmaceutical Industry. 

Job Summary

We are seeking a highly skilled AI Engineer to design, build, and deploy next-generation AI solutions that transform clinical trial operations for Clinical Research Group (CRG).This role focuses on building AI-powered platforms and agentic automation systems that accelerate clinical trials, improve data quality, and reduce operational burden across study start up, patient enrollment, monitoring, and regulatory submissions. The AI Engineer will collaborate with clinical domain experts, data engineers, product teams, and platform architects to develop scalable AI solutions that integrate with modern clinical data ecosystems, including CTMS, EDC, eTMF and real world data platforms.

Key Responsibilities

Build AI Solutions for Clinical Trial Operations 

Design and implement AI models and systems that improve clinical operations, including:

• Patient enrollment forecasting
• Protocol optimization
• Clinical site performance prediction
• Risk-based monitoring automation
• Clinical document intelligence
• Operational forecasting and simulation

Example solutions include:

• AI-powered Clinical Trial Forecasting Suite (CTFS) for predicting enrollment timelines
• Agentic AI assistants supporting Clinical Research Associates (CRAs)
• Document intelligence systems extracting insights from protocols, investigator brochures, and regulatory submissions
  
  

Develop Agentic AI Systems

Design multi-agent AI workflows that automate complex clinical processes.

Example use cases include:

• AI agents reviewing monitoring reports and generating insights
• Automated protocol feasibility assessments
• Intelligent clinical data quality monitoring
• Study risk detection across trial sites

Key capabilities include:

• Agent orchestration frameworks
• Retrieval-Augmented Generation (RAG) pipelines
• Autonomous workflow orchestration
• Guardrails and compliance monitoring
  
  

Build Scalable AI Platforms

Develop production-grade AI systems integrated with enterprise clinical platforms.

Key integrations include:

• Clinical Trial Management Systems (CTMS)
• Electronic Data Capture (EDC) systems
• eTMF document management platforms
• Safety and pharmacovigilance systems
• Real-world data sources

Responsibilities include:

• Model deployment pipelines
• MLOps frameworks
• Scalable API development
• Cloud-native AI infrastructure

Work on Advanced AI Models:

Develop and deploy advanced AI capabilities including:

• Predictive ML models for clinical forecasting
• LLM-powered clinical copilots
• Knowledge graph–enabled RAG systems
• Simulation models for trial design optimization

Techniques include:

• Deep learning
• Graph AI
• Time-series forecasting
• NLP for clinical documents
• Generative AI for clinical insights

Ensure Compliance & Responsible AI

Ensure AI systems meet life sciences regulatory requirements, including:

• GxP compliance
• Data privacy standards
• Auditability and traceability
• Model validation frameworks

Work closely with clinical stakeholders to ensure solutions are trustworthy, compliant, and explainable.

Qualifications

Education : Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence / Machine Learning, Data Science, Bioinformatics Or a related technical field

Technical Skills 

Programming

• Python
• SQL
• APIs / microservices

AI / Machine Learning

• Machine learning frameworks (PyTorch, TensorFlow, Scikit-learn)
• LLM frameworks (LangChain, LlamaIndex, OpenAI APIs)
• Retrieval-Augmented Generation (RAG)

Data Platforms

• Data pipelines
• Vector databases (Pinecone, Chroma, Weaviate)
• Knowledge graphs / graph databases

Cloud Platforms

• AWS / Azure / Google Cloud Platform
• Containerization (Docker, Kubernetes)

MLOps

• Model deployment
• CI/CD for AI
• Monitoring and observability

Domain Knowledge 

Experience in life sciences or healthcare data environments, including familiarity with:

• Clinical trial operations
• CTMS / EDC / eTMF systems
• Clinical data standards (CDISC, SDTM, ADaM)
• Regulatory frameworks (GxP)

Preferred experience with:

• Agentic AI architectures
• Digital twins or simulation systems
• Clinical data analytics
• Clinical trial optimization models
• Large enterprise platform development

Why Join This Team 

• You will work at the intersection of AI innovation, Clinical research, Large-scale digital transformation
• This role provides an opportunity to build cutting edge AI platforms that shape the future of clinical trials and drug development.