python developer for generative AI applications

Pfizer is a pharmaceutical manufacturing company.

• Define the technical strategy and architecture for Python-based AI backend platforms supporting LLM integration, generative AI pipelines, and AI agent orchestration
• Architect scalable, reliable, and secure AWS systems that provide a foundation for multiple teams
• Drive technical decisions affecting organization-wide engineering practices and platform capabilities
• Design and champion AI system observability
• Establish standards for monitoring, logging, observability, and operational excellence across AI backend services
• Lead cross-functional initiatives to optimize the performance, security, and scalability of large-scale AI applications
• Mentor and technically guide engineers through code reviews, architecture reviews, and technical leadership
• Identify technical debt, performance bottlenecks, and architectural limitations, and drive long-term solutions
• Collaborate with engineering leadership, product, and other stakeholders to align technical strategy with business objectives
• Influence technology choices, design patterns, and best practices across the AI Software & Operations department
• Represent the team in organization-wide technical discussions and drive adoption of innovative solutions

• 7+ Years of professional software engineering experience, with extensive backend and distributed systems expertise
• Expert-level proficiency in Python for building large-scale production systems
• Comprehensive understanding of LLMs, generative AI architectures, and AI infrastructure
• Proven track record of architecting and delivering complex, scalable platforms on AWS
• Expert knowledge of microservices architecture, distributed systems design, and event-driven architectures
• Experience with containerization, orchestration, and cloud-native patterns
• Strong technical leadership and mentoring experience, with a record of driving organizational impact
• Bachelor's or Master's degree in Computer Science, Engineering, or a related field, or equivalent practical experience
• Strong strategic thinking and ability to balance short-term delivery with long-term architectural vision
• Будет плюсом: experience building AI/ML platform infrastructure at scale, FastAPI, asynchronous Python, high-performance backend systems, event-driven and real-time AI systems, influencing engineering culture and establishing technical standards, MLOps, model deployment, AI system reliability, infrastructure-as-code, CI/CD automation, platform engineering, translating product and business requirements into technical strategy, leading cross-functional technical initiatives with measurable organizational impact, published technical work, open-source contributions, recognized expertise in AI backend systems, exceptional communication and influence skills

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