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 Technical Lead in the newly formed AIA team, we are looking for a hands-on solution architect to lead the design and implementation of end-to-end agentic AI solutions at enterprise scale. This role requires expertise across AI architecture, cloud engineering, data platforms, MLOps/LLOps and product thinking. The ideal candidate should be comfortable engaging directly with business stakeholders, translating ambiguous needs into technical solutions, developing MVPs and guiding engineering team toward scalable delivery.
Role Responsibilities
Solution Design & Architecture
- Architect enterprise-grade AI solutions integrating LLMs, RAG, autonomous agents, vector search, orchestration frameworks, APIs and UI layers
- Implements scalable E2E AI pipelines- data-> semantic layer-> embeddings-> vector DB-> inference-> monitoring
- Own architecture documentation, solutions diagrams and technical decision logs
- Act as player coach-able to prototype agents, build POCs and guide engineering teams production systems
Cross-Functional Collaboration
- Partner with Product Owners, Data Scientists, Engineers, and Business Stakeholders to translate requirements into technical solutions.
- Facilitate workshops and design sessions to gather insights and co-create technical solution blueprints.
- Ensure integration of AI solutions with existing enterprise systems and data environment. Push boundaries of technical innovation at the enterprise level.
Technical Leadership & Governance
- Define and enforce architectural standards, best practices, and design patterns for AI and digital health solutions.
- Set the standard for and lead technical reviews, risk assessments, and design validations.
- Ensure solutions adhere to data privacy, security, and regulatory requirements (e.g., HIPAA, GDPR, ANVISA, COFEPRIS).
- Ensure security, scalability, privacy safeguards, hallucination risk control and responsible AI implementation
- Establish guardrails for model usage, evaluation metrics, monitoring and fallback plans
Innovation & Emerging Technologies
- Stay abreast of emerging AI technologies, platforms, and trends relevant to healthcare and life sciences.
- Evaluate and prototype new tools (e.g., LLMs, federated learning, edge AI) for potential adoption.
- Drive innovation by identifying opportunities for AI to enhance patient outcomes, operational efficiency, and market differentiation.
- Documentation & Knowledge Management
- Develop and maintain comprehensive architecture documentation, including diagrams, data flows, and technical specifications.
- Create reusable solution templates and reference architectures for future projects. Develop platform strategies to empower teams with consistent and re-usable patterns
- Contribute to internal knowledge bases and technical communities of practice.
- Vendor & Partner Engagement
- Assess and manage relationships with external technology vendors, cloud providers, and implementation partners.
- Lead technical due diligence and integration planning for third-party AI solutions.
- Ensure vendor solutions align with internal architecture and compliance standards.
Basic Qualifications
- Bachelor’s degree in Computer Science, Engineering, data Science or related field.
- 9+ years of relevant experience in AI/ML/Data/SaaS engineering roles with 2+ years in architecture capacity
- Proven experience in designing and deploying AI solutions in healthcare or regulated industries.
- Deep understanding of cloud platforms (e.g., Azure, AWS, GCP), microservices, APIs, and data engineering.
- Familiarity with AI/ML frameworks (e.g., TensorFlow, PyTorch), MLOps, and model lifecycle management.
- Hands-on experience with
- Data Tech: Snowflake/Kafka/Spark
- APIs & Microservices: Python, FastAPI, REST
- MLOps/LLMOps: MLflow, Vertex AI
- LLMs, RAG, LangGraph/OpenAI
- Excellent communication, stakeholder management, and analytical skills.
- 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.
- Experience with Agentic AI frameworks (CrewAI, AutoGen, Hugging Face agents, OpenAI workflows)
- Familiarity with compliance standards such as GxP, HIPAA, and data privacy regulations.
- Knowledge of enterprise workflow tools – Salesforce, ServiceNow, SAP, Veeva etc
- Demonstrated success in deploying AI or ML solutions in production environments.
Pfizer is an equal opportunity employer and complies with all applicable equal employment opportunity legislation in each jurisdiction in which it operates.
Information & Business Tech
