At EVERSANA, we are proud to be certified as a Great Place to Work across the globe. We’re fueled by our vision to create a healthier world. How? Our global team of more than 7,000 employees is committed to creating and delivering next-generation commercialization services to the life sciences industry. We are grounded in our cultural beliefs and serve more than 650 clients ranging from innovative biotech start-ups to established pharmaceutical companies. Our products, services and solutions help bring innovative therapies to market and support the patients who depend on them. Our jobs, skills and talents are unique, but together we make an impact every day. Join us!
Across our growing organization, we embrace diversity in backgrounds and experiences. Improving patient lives around the world is a priority, and we need people from all backgrounds and swaths of life to help build the future of the healthcare and the life sciences industry. We believe our people make all the difference in cultivating an inclusive culture that embraces our cultural beliefs. We are deliberate and self-reflective about the kind of team and culture we are building. We look for team members that are not only strong in their own aptitudes but also who care deeply about EVERSANA, our people, clients and most importantly, the patients we serve. We are EVERSANA.
We are seeking a highly motivated AI Engineer with 5+ years of experience in Artificial Intelligence, Machine Learning, Generative AI, and Agentic Engineering to join our Pharmacovigilance Technology team.
The ideal candidate will work closely with Pharmacovigilance SMEs, Product Owners, Data Scientists, Safety Operations Teams, and Software Engineers to design, develop, and deploy AI-powered solutions that enhance drug safety monitoring, adverse event case processing, signal detection, literature surveillance, regulatory reporting, and medical document intelligence.
This role offers an opportunity to shape next-generation AI products leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), NLP, Machine Learning, and Agentic AI frameworks within the Life Sciences domain.
ESSENTIAL DUTIES AND RESPONSIBILITIES
Our employees are tasked with delivering excellent business results through the efforts of their teams. These results are achieved by:
AI Solution Development
- 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 PV operations and safety case management.
- Build intelligent document processing solutions for source documents, ICSRs, safety narratives, and regulatory reports.
Large Language Models & GenAI
- 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.
Data Engineering & Integration
- Collaborate with data engineers to integrate safety systems and clinical data sources.
- Develop data pipelines for structured and unstructured PV data.
- Integrate APIs and enterprise applications into AI workflows.
- Work with structured and graph-based data sources to support advanced AI applications.
MLOps & Deployment
- Deploy AI models and GenAI applications into production environments.
- Implement monitoring, model evaluation, drift detection, and performance optimization.
- Maintain scalable, secure, and compliant AI infrastructure.
- Implement observability and telemetry for AI/ML applications and services using OpenTelemetry.
- Support CI/CD and automated deployment pipelines for AI applications.
Compliance & Governance
- 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.
Stakeholder Collaboration
- 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.
MINIMUM KNOWLEDGE, SKILLS AND ABILITIES
The requirements listed below are representative of the experience, education, knowledge, skill and/or abilities required.
Education
- 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 is highly valued.
- Candidates with advanced degrees are encouraged to apply; however, 5+ years of relevant hands-on industry experience remains the primary experience requirement.
Experience
- 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.
- Experience working in Healthcare, Life Sciences, Clinical, or Pharmacovigilance domains is preferred.
Technical Skills
Programming / Databases
- Python – Mandatory
- SQL
- REST APIs
- PostgreSQL
AI / ML
- Machine Learning
- Deep Learning
- Transformer Models
- Generative AI
- LLM Fine-Tuning
- NLP
GenAI Ecosystem
- Azure OpenAI / OpenAI APIs
- LangChain
- Agentic AI frameworks – Mandatory
- crewAI
- LlamaIndex
- Prompt Engineering
- RAG Architecture
- Semantic Search
- Vector Databases
Cloud Platforms
- GCP – Preferred
- Azure
- AWS
MLOps / Infrastructure
- MLflow
- Docker
- Kubernetes
- CI/CD Pipelines
- OpenTelemetry
PREFERRED QUALIFICATIONS
- 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.
Preferred Domain Knowledge
- Pharmacovigilance
- Drug Safety
- Clinical Research
- Clinical Trials
- Regulatory Affairs
- Life Sciences
- Healthcare
- GxP / GVP environments
- FDA / EMA / MHRA regulatory ecosystems
OUR CULTURAL BELIEFS:
Patient Minded I act with the patient’s best interest in mind.
Client Delight I own every client experience and its impact on results.
Take Action I am empowered and empower others to act now.
Grow Talent I own my development and invest in the development of others.
Win Together I passionately connect with anyone, anywhere, anytime to achieve results.
Communication Matters I speak up to create transparent, thoughtful and timely dialogue.
Embrace Diversity I create an environment of awareness and respect.
Always Innovate I am bold and creative in everything I do.
Our team is aware of recent fraudulent job offers in the market, misrepresenting EVERSANA. Recruitment fraud is a sophisticated scam commonly perpetrated through online services using fake websites, unsolicited e-mails, or even text messages claiming to be a legitimate company. Some of these scams request personal information and even payment for training or job application fees. Please know EVERSANA would never require personal information nor payment of any kind during the employment process. We respect the personal rights of all candidates looking to explore careers at EVERSANA.
From EVERSANA’s inception, Diversity, Equity & Inclusion have always been key to our success. We are an Equal Opportunity Employer, and our employees are people with different strengths, experiences, and backgrounds who share a passion for improving the lives of patients and leading innovation within the healthcare industry. Diversity not only includes race and gender identity, but also age, disability status, veteran status, sexual orientation, religion, and many other parts of one’s identity. All of our employees’ points of view are key to our success, and inclusion is everyone's responsibility.
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