The AI Engineer will design and deploy AI agents, develop LLMs, build robust model pipelines, and integrate solutions while ensuring compliance and performance optimization.
ROLE SUMMARY
The AI Acceleration (AIA) function within the Chief Marketing Office (CMO) is the single, business-led engine that owns the design, delivery, and scale-up of priority AI capabilities across Commercial. AIA works in tight collaboration with various Pfizer functions to deploy and maintain production-grade AI solutions that simplify how we work and drive measurable value across all processes.
As a AI engineer in the newly formed AIA team, you will design, build and deploy AI agents that automate workflows, enhance decision-making, and enable intelligent user interactions across the enterprise. This role will focus on integrating multi-agent frameworks and ensuring scalable, ethical, and high-performance agent-based systems.
Agentic AI & LLM development
RAG & Knowledge Creation
Model Engineering & MLOps/LLMOps
Integration and Application Development
Collaboration & Innovation
BASIC QUALIFICATIONS
Preferred Qualifications:
Pfizer is an equal opportunity employer and complies with all applicable equal employment opportunity legislation in each jurisdiction in which it operates.
Marketing and Market Research
The AI Acceleration (AIA) function within the Chief Marketing Office (CMO) is the single, business-led engine that owns the design, delivery, and scale-up of priority AI capabilities across Commercial. AIA works in tight collaboration with various Pfizer functions to deploy and maintain production-grade AI solutions that simplify how we work and drive measurable value across all processes.
As a AI engineer in the newly formed AIA team, you will design, build and deploy AI agents that automate workflows, enhance decision-making, and enable intelligent user interactions across the enterprise. This role will focus on integrating multi-agent frameworks and ensuring scalable, ethical, and high-performance agent-based systems.
Agentic AI & LLM development
- Design, build and optimize LLM-driven agents, multi agent systems and autonomous AI workflows
- Develop domain-specific toolkits, prompt pipeline and agent orchestration logic
- Implement safety, guardrails, fallback patterns and hallucination control strategies
RAG & Knowledge Creation
- Architect and implement retrieval-augmented generation pipelines with embeddings, vector search and metadata filtering
- Work closely with data engineering to build semantic layers, knowledge graphs and ontology aligned datasets
- Fine-tune and adapt LLMs using domain-specific knowledge while ensuring compliance
Model Engineering & MLOps/LLMOps
- Develop and tune ML/LLM models
- Build robust model pipelines for training, evaluation, deployment and monitoring
- Implements LLMOps practices-lineage, versioning, bias/hallucination evaluation, prompt testing and runtime monitoring
Integration and Application Development
- Develop APIs, microservices and agent endpoints for enterprise integration
- Utilize cloud infrastructure (Azure/AWS/GCP) and MLOps frameworks for continuous delivery.
- Ensure code quality, testing, and maintainability through best development practices. .
- Continuously optimize performance and cost efficiency of AI systems.
Collaboration & Innovation
- Partner with Business Translators, UI/UX, and Change Management teams to translate needs into deployable AI solutions.
- Evaluate new technologies and frameworks that enhance automation or predictive insights.
- Drive innovation through hackathons, proof-of-concepts, and partnerships with vendors.
- Promote a culture of responsible AI, ethics, and compliance
BASIC QUALIFICATIONS
- Bachelor's degree in Computer Science, Engineering, or related field.
- 5+ years of relevant experience in AI, software, or data development.
- Experience with agentic orchestration frameworks (e.g. Langchain), Vector databases (e.g. pinecone), embedding models, RAG architecture, and LLM principles.
- Proven leadership in managing technical teams and delivering enterprise-scale projects.
- Strong knowledge of agile methodologies and DevOps practices.
Preferred Qualifications:
- Master's degree or PhD in Computer Science, Data Science, or related field.
- Experience in pharmaceutical or healthcare technology environments.
- Familiarity with compliance standards such as GxP, HIPAA, and data privacy regulations.
- Demonstrated success in deploying AI or ML solutions in production environments.
- Understanding of commercial analytics, medical content and scientific knowledge workflows
- Familiarity with prompt evaluation frameworks
Pfizer is an equal opportunity employer and complies with all applicable equal employment opportunity legislation in each jurisdiction in which it operates.
Marketing and Market Research
Top Skills
AI
AWS
Azure
DevOps
GCP
Langchain
Llm
Mlops
Pinecone
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What you need to know about the Melbourne Tech Scene
Home to 650 biotech companies, 10 major research institutes and nine universities, Melbourne is among one of the top cities for biotech. In fact, some of the greatest medical advancements were conceptualized and developed here, including Symex Lab's "lab-on-a-chip" solution that monitors hormones to predict ovulation for conception, and Denteric's vaccine for periodontal gum disease. Yet, the thousands of people working in the city's healthtech sector are just getting started, to say nothing of the tech advancements across all other sectors.

