Overview

As AI Backend Python Engineer (Staff), you define and lead the architecture for scalable backend platforms powering generative AI and LLM integrations. You’ll shape platform-level solutions on Python, FastAPI, and AWS, influencing engineering practices across Pfizer's AI Software & Operations group. You’ll tackle observability, security, and performance at scale, working with cross-functional teams to align technical strategy with business goals. This role offers the opportunity to drive lasting impact on AI infrastructure and engineering culture, at a global pharmaceutical leader.

Retribuzione / Benefits

- remote work

Responsabilità

- Define technical strategy and architecture for Python-based AI backends with LLM integration
- Architect scalable, secure AWS-based systems (Lambda, EKS) for multiple teams
- Drive organization-wide engineering practice decisions and platform capabilities
- Champion AI observability using LangChain, Langfuse, and litellm
- Establish monitoring, logging, and operational excellence standards
- Lead cross-functional initiatives to improve performance, security, and scalability
- Mentor engineers through reviews and technical leadership
- Identify and address technical debt, bottlenecks, and architectural gaps

- Collaborate with leadership, product, and stakeholders to align strategy with business objectives
- Influence technology choices and best practices across the AI Software & Operations department
- Represent the team in organization-wide technical discussions and drive adoption of innovative solutions

Requisiti fondamentali

- 7+ years of backend and distributed systems experience
- Expert-level Python for large-scale production systems
- Deep understanding of LLMs, generative AI architectures, and AI infrastructure (LangChain, litellm, Langfuse, OpenAI/Anthropic APIs)
- Proven track record delivering complex, scalable platforms on AWS
- Expert knowledge of microservices, distributed systems, and event-driven architectures
- Experience with containers and orchestration (Docker/Kubernetes) and cloud-native patterns
- Strong history of technical leadership and mentoring
- Degree in Computer Science, Engineering, or related field, or equivalent experience
- Strategic thinking with balance of short-term delivery and long-term architecture

- strong communication
- influence and collaboration
- mentoring
- FastAPI
- asynchronous Python
- AWS (Lambda, EKS)

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