The Applied AI Scientist — R&D and Regulatory builds and deploys AI systems that accelerate product development and regulatory submissions. The role applies natural language processing, document intelligence, and generative AI to Amneal's scientific and regulatory content, delivering validated systems that meet GxP and 21 CFR Part 11 requirements and are defensible under health authority inspection. The role sits within the Enterprise AI Transformation function, working in close partnership with Regulatory Affairs and R&D.
Essential Functions:
Regulatory & Scientific Agents
- Build models that analyze historical health authority correspondence — deficiency letters, information requests, and complete response letters — to identify recurring deficiency patterns and flag submission risk prior to filing.
- Develop retrieval and generation agentic systems over controlled scientific content including specifications, analytical methods, stability data, prior filings, and eCTD, with full traceability from output to source.
- Build AI-assisted drafting and comparison capability for product labeling, including structured product labeling content and reference listed drug comparison.
AI Solution Development
- Design and maintain formal evaluation frameworks for all generative systems, including curated golden datasets, defined failure taxonomies, and automated regression testing.
- Execute AI system validation under Amneal's GxP AI validation framework: risk classification, intended-use definition, qualification testing, and periodic review.
- Build and maintain production data pipelines on Databricks over unstructured scientific documents, including OCR, parsing, and entity extraction from legacy PDF sources.
Business Impact
- Establish benefit baselines with Regulatory and R&D functional owners and measure realized cycle-time and capacity outcomes.
- Present technical approaches, validation evidence, and model limitations to Regulatory, and R&D leadership.
- Enable larger organization and educate to upskill on usage and application of agentic systems.
Research and Portfolio Insights
- Develop literature, patent, and prior-art mining capabilities supporting product development screening and portfolio prioritization.
Education:
- Bachelor's Degree (BA/BS) Computer Science, Computational Chemistry, Bioinformatics, Statistics or a related quantitative or scientific field, with equivalent demonstrated experience (Required)
- Master's Degree (MS/MA) Computer Science, Computational Chemistry, Bioinformatics, Statistics or a related quantitative or scientific field (Preferred)
- Ph. D. Computer Science, Computational Chemistry, Bioinformatics, Statistics or a related quantitative or scientific field (Preferred)
Experience:
- 5 years or more in Developing and deploying machine learning or AI systems in a production environment
- 5 years or more in Advanced proficiency with Python, agentic frameworks
- 5 years or more in Hands on experience building and evaluating LLM and agentic applications including retrieval-augmented generation, structured output, tool use, multi-step agent orchestration, and quantitative evaluation
- 5 years or more in NLP experience over technical or scientific text, including document parsing, information extraction and semantic search
- 5 years or more in AI system validation or AI governance in a regulated industry
Specialized Knowledge:
- • Demonstrated ability to work within documented, controlled processes and produce audit-quality technical documentation (required)
- • Databricks (Unity Catalog, Delta Lake, MLflow) and cloud ML platforms such as Amazon Bedrock or SageMaker (preferred)
- • Knowledge / experience with GxP-regulated environment; familiarity with 21 CFR Part 11, computerized system validation, or GAMP 5 (preferred)
- • Knowledge of ANDA, NDA, or DMF submission content, eCTD structure, or health authority correspondence (preferred)
The salary range for this position ranges from $190,000 - $225,000 per year. In addition, Amneal offers a short-term incentive opportunity, such as a bonus or performance-based award with this position within the first 12 months. Amneal ranges reflect the Company’s good faith estimate of what Amneal reasonably believes that it will pay for said position at the time of the posting. Individual compensation will ultimately be determined based on a variety of relevant factors, including but not limited to, qualifications, experience, geographic location and other relevant skills.
At the heart of our Total Rewards commitment is a comprehensive, flexible and competitive benefits program for eligible positions that enables you to choose the plans and coverage that meet your personal needs. This includes above-market, diverse and robust health and insurance benefits to meet the varied needs of our employees as well as a significant 401(k) matching contribution to help our employees save for retirement. We also promote employee well-being with programs that help you enjoy your career alongside life’s many other commitments and opportunities.