Sr AI Engineer (Generative AI & Pharmacovigilance)
RemoteUnited States or India
Job Summary
Design, develop, and deploy AI/ML solutions for Pharmacovigilance business processes using Large Language Models, Retrieval-Augmented Generation, and Agentic AI frameworks. Build intelligent document processing systems for source documents, ICSRs, and safety narratives while collaborating with Pharmacovigilance SMEs to translate regulatory requirements into scalable applications. Develop and optimize RAG-based architectures, fine-tune domain-specific models, and implement evaluation strategies for AI agents and workflow automation. Integrate safety systems and clinical data sources through data pipelines and APIs, then deploy models into production environments with observability and telemetry. Ensure all solutions comply with GxP, FDA, and EMA standards while maintaining secure, compliant infrastructure.
Required Qualifications
- 5+ years of hands-on experience in AI/ML engineering
- Experience developing and deploying production-grade AI applications
- Mandatory experience developing solutions using Agentic AI frameworks
- Experience with Generative AI, LLMs, RAG, NLP, and AI/ML application development
- Experience working with cloud platforms and production AI/ML deployment environments
- Python – Mandatory
- SQL
- REST APIs
- PostgreSQL
- Machine Learning
- Deep Learning
- Transformer Models
- Generative AI
- LLM Fine-Tuning
- NLP
- Azure OpenAI / OpenAI APIs
- LangChain
- Agentic AI frameworks – Mandatory
- crewAI
- LlamaIndex
- Prompt Engineering
- RAG Architecture
- Semantic Search
- Vector Databases
- Azure
- AWS
- MLflow
- Docker
- Kubernetes
- CI/CD Pipelines
- OpenTelemetry
- Bachelor's degree in Computer Science, Data Science, Artificial Intelligence, Engineering, Physics, Bioinformatics, or a related discipline
- Master's or PhD in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Physics, Engineering, Bioinformatics, or a related discipline
- 5+ years of relevant hands-on industry experience
Desired Qualifications
- Master's or PhD in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Physics, Engineering, Bioinformatics, or a related discipline is highly valued
- Candidates with advanced degrees are encouraged to apply
- Experience working in Healthcare, Life Sciences, Clinical, or Pharmacovigilance domains is preferred
- Good understanding of Pharmacovigilance processes such as ICSR intake, case processing, submission, aggregate reports, signal detection, etc.
- Experience with Graph Databases and GraphRAG
- Knowledge of Clinical Trial and Regulatory ecosystems
- Experience working in GxP-validated environments
- Experience implementing AI solutions within regulated Healthcare or Life Sciences environments
- Experience with AI observability, evaluation, monitoring, and model governance
- GCP – Preferred
- Pharmacovigilance
- Drug Safety
- Clinical Research
- Clinical Trials
- Regulatory Affairs
- Life Sciences
- Healthcare
- GxP / GVP environments
- FDA / EMA / MHRA regulatory ecosystems
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