Senior AI Engineer – Generative AI, Pharmacovigilance

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EVERSANA

WebsiteLinkedInAll Job Openings

5001 - 10000 employees

💼 Consulting

🏥 Healthcare

⚕️ Healthcare Insurance

Consulting • Healthcare • Healthcare Insurance

EVERSANA is a comprehensive service provider focused on integrated commercial solutions for the life sciences industry. The company offers a wide range of services including advisory and management consulting, regulatory consulting, patient services, market access strategies, pricing and revenue management, medical affairs, and digital transformation. EVERSANA is known for its expertise in drug commercialization, enabling companies to effectively launch and manage pharmaceutical products. With a platform powered by data and analytics, EVERSANA addresses challenges related to drug pricing, market access, patient adherence, and product delivery, helping companies optimize their commercial strategies and enhance patient outcomes. The company emphasizes innovation and has been recognized for its use of AI and data analytics within the life sciences sector.

📋 Description

• Design, develop, and deploy AI/ML solutions for Pharmacovigilance business processes • Build Generative AI applications using OpenAI, Azure OpenAI, Anthropic, Llama, or equivalent LLM platforms • Develop domain-specific AI assistants for Pharmacovigilance operations and safety case management • Build intelligent document processing solutions for source documents, ICSRs, safety narratives, and regulatory reports • Build and optimize RAG-based applications using vector databases • Develop prompt engineering frameworks and evaluation methodologies • Fine-tune domain-specific models using pharmacovigilance datasets • Develop AI agents and workflow automation capabilities using Agentic AI frameworks • Develop and implement evaluation strategies for LLM and Agentic AI applications • Integrate safety systems, clinical data sources, APIs, and enterprise applications into AI workflows • Develop data pipelines for structured and unstructured Pharmacovigilance data • Work with structured and graph-based data sources to support advanced AI applications • Deploy AI models and Generative AI applications into production environments • Implement monitoring, model evaluation, drift detection, performance optimization, observability, and telemetry using OpenTelemetry • Maintain scalable, secure, and compliant AI infrastructure • Support CI/CD and automated deployment pipelines for AI applications • Ensure AI solutions comply with GxP, GVP, FDA, EMA, MHRA, and internal quality standards • Support AI validation, audit readiness, traceability, and documentation requirements • Implement Responsible AI and model governance practices • Partner with Pharmacovigilance SMEs and Product Managers to understand business requirements • Translate regulatory and safety requirements into scalable AI solutions • Support demos, proof-of-concepts, and innovation initiatives

🎯 Requirements

• Bachelor’s degree in Computer Science, Data Science, Artificial Intelligence, Engineering, Physics, Bioinformatics, or a related discipline • 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 and Deep Learning • Transformer Models • Generative AI, LLM, and fine-tuning • NLP • Azure OpenAI / OpenAI APIs • LangChain • Agentic AI frameworks — mandatory • crewAI • LlamaIndex • Prompt Engineering • RAG Architecture • Semantic Search • Vector Databases • Azure and AWS; GCP preferred • MLflow • Docker • Kubernetes • CI/CD Pipelines • OpenTelemetry • Understanding of Pharmacovigilance processes is preferred • Experience with Graph Databases and GraphRAG is preferred • Knowledge of Clinical Trial and Regulatory ecosystems is preferred • Experience working in GxP-validated environments is preferred • Experience implementing AI solutions within regulated Healthcare or Life Sciences environments is preferred • Experience with AI observability, evaluation, monitoring, and model governance is preferred

🏖️ Benefits

• Certified as a Great Place to Work • Equal Opportunity Employer • Diversity, Equity & Inclusion commitment • Remote work option • Professional development and investment in employee development • Opportunity to work on next-generation AI products and innovation initiatives