AI Data Engineer--LLMs / Agentic Systems
Pfizer
3 months ago
Remote friendly (Cambridge, MA)
United States
IT
Position Responsibilities
- Design and implement production-grade full stack applications integrating LLM/AI into scientific workflows.
- Collaborate with medicinal chemists, biomedical researchers, and domain experts to translate scientific needs into technical solutions.
- Build scalable Python backend services for data processing, embedding generation, vector search, and LLM orchestration.
- Develop responsive frontends using React and TypeScript.
- Implement RAG systems, conversational AI interfaces, and agentic LLM architectures for pharmaceutical knowledge work automation.
- Deploy and maintain production systems on AWS with reliability, performance, scalability, and UX focus.
- Iterate continuously based on user feedback and evolving AI/LLM capabilities.
- Integrate semantic search technologies, vector databases, and embedding models.
- Contribute to novel semantic frameworks for drug discovery.
- Support cross-functional communication, documentation, and knowledge sharing.
Basic Qualifications
- PhD in Biology, Chemistry, Pharmacology, Toxicology, Computer Science, or related field; or Master’s degree with 2+ years building AI-powered research applications.
- Strong technical problem solving; translate complex scientific requirements into technical solutions.
- 2+ years programming in Python and TypeScript; production-quality software.
- Portfolio of production full stack apps (Python backends, React frontends; GitHub required).
- Experience with FastAPI and React.
- Excellent written/verbal/presentation communication and cross-functional collaboration.
Preferred Qualifications
- Life sciences/pharma/drug discovery/cheminformatics interest.
- LLM frameworks (OpenAI API, Hugging Face Transformers, Anthropic Claude); prompt engineering and LLM optimization.
- Conversational/agentic AI experience.
- Vector DBs/semantic search; MongoDB/PostgreSQL.
- PyTorch deep learning experience (NLP/CV).
- AWS (EC2, S3, CloudFormation, RDS), DevOps, Docker, CI/CD (GitHub Actions/Jenkins/GitLab CI).
Physical/Mental Requirements
- Strong system design and sustained analytical thinking; rapid context-switching across technical and scientific domains.
Schedule/Travel
- Flexibility across time zones; occasional travel may be required.
- Hybrid: on-site ~2.5 days/week or more as needed.
Compensation/Benefits (as stated)
- Base salary: $106,000–$176,600.
- Eligible for Global Performance Plan bonus target 15% and share-based long-term incentives.
- 401(k) with matching, paid vacation/holidays/personal days, paid caregiver/parental and medical leave, and medical/dental/vision benefits.
Relocation and visa
- Relocation assistance may be available.
- U.S. work visa sponsorship is not available.
- Design and implement production-grade full stack applications integrating LLM/AI into scientific workflows.
- Collaborate with medicinal chemists, biomedical researchers, and domain experts to translate scientific needs into technical solutions.
- Build scalable Python backend services for data processing, embedding generation, vector search, and LLM orchestration.
- Develop responsive frontends using React and TypeScript.
- Implement RAG systems, conversational AI interfaces, and agentic LLM architectures for pharmaceutical knowledge work automation.
- Deploy and maintain production systems on AWS with reliability, performance, scalability, and UX focus.
- Iterate continuously based on user feedback and evolving AI/LLM capabilities.
- Integrate semantic search technologies, vector databases, and embedding models.
- Contribute to novel semantic frameworks for drug discovery.
- Support cross-functional communication, documentation, and knowledge sharing.
Basic Qualifications
- PhD in Biology, Chemistry, Pharmacology, Toxicology, Computer Science, or related field; or Master’s degree with 2+ years building AI-powered research applications.
- Strong technical problem solving; translate complex scientific requirements into technical solutions.
- 2+ years programming in Python and TypeScript; production-quality software.
- Portfolio of production full stack apps (Python backends, React frontends; GitHub required).
- Experience with FastAPI and React.
- Excellent written/verbal/presentation communication and cross-functional collaboration.
Preferred Qualifications
- Life sciences/pharma/drug discovery/cheminformatics interest.
- LLM frameworks (OpenAI API, Hugging Face Transformers, Anthropic Claude); prompt engineering and LLM optimization.
- Conversational/agentic AI experience.
- Vector DBs/semantic search; MongoDB/PostgreSQL.
- PyTorch deep learning experience (NLP/CV).
- AWS (EC2, S3, CloudFormation, RDS), DevOps, Docker, CI/CD (GitHub Actions/Jenkins/GitLab CI).
Physical/Mental Requirements
- Strong system design and sustained analytical thinking; rapid context-switching across technical and scientific domains.
Schedule/Travel
- Flexibility across time zones; occasional travel may be required.
- Hybrid: on-site ~2.5 days/week or more as needed.
Compensation/Benefits (as stated)
- Base salary: $106,000–$176,600.
- Eligible for Global Performance Plan bonus target 15% and share-based long-term incentives.
- 401(k) with matching, paid vacation/holidays/personal days, paid caregiver/parental and medical leave, and medical/dental/vision benefits.
Relocation and visa
- Relocation assistance may be available.
- U.S. work visa sponsorship is not available.