Hybrid Staff Software Engineer – AI

at Snowflake

• Job title: Staff Software Engineer – AI
• Job type: Full Time
• Experience level: Lead
• Salary: Not specified
• Degree requirement: Postgraduate Degree
• Tech skills: Cloud, Distributed Systems, Docker, GRPC, Kubernetes, Python
• Location requirements: Hybrid, Warsaw, Poland

About the role

• Staff Software Engineer developing and operating AI-powered services at Snowflake. Shaping system architecture and mentoring engineers to elevate technical quality and collaboration.

Responsibilities

• Act as a technical leader and force multiplier, combining hands-on engineering with architectural and strategic influence.
• Architect and drive the development of large-scale AI platforms and services, including LLM- and multimodal-based systems integrated into the Snowflake Data Cloud.
• Own end-to-end technical design of critical systems across APIs, SDKs, distributed services, control planes, and production deployments.
• Lead the resolution of complex, cross-team engineering problems spanning multiple services and organizations.
• Define and evolve technical standards, best practices, and architectural patterns for AI-related systems.
• Partner closely with research, product, infrastructure, and security teams to translate research and business requirements into scalable, production-ready solutions.
• Influence short- and long-term platform strategy through architectural reviews, technical roadmaps, and prioritization decisions.
• Mentor engineers to raise technical quality and decision-making maturity across teams.
• Serve as a technical advisor to leadership, clearly articulating trade-offs, risks, and system-level implications.
• Drive operational excellence across reliability, security, performance, and cost efficiency.

Requirements

• 8+ years of experience building and operating production-grade, distributed systems at scale.
• Expert-level backend development skills, with Python strongly preferred.
• Proven experience designing and owning public-facing SDKs and service APIs (REST and/or gRPC), including versioning, backward compatibility, and reliability.
• Strong foundation in distributed systems, including concurrency, fault tolerance, scalability, and performance optimization.
• Hands-on experience building AI/ML platforms, such as model inference services, data pipelines, feature stores, or AI-centric APIs.
• Solid understanding of LLM and NLP system requirements (latency, throughput, observability, cost controls) and ability to bring research prototypes to production.
• Deep familiarity with modern software engineering practices, including CI/CD, automated testing, infrastructure as code, Docker, Kubernetes, and cloud-native deployments.
• Strong focus on operability and reliability, including monitoring, alerting, debugging, and incident response.
• Experience designing or operating control-plane and data-plane services is a strong plus.
• Demonstrated technical leadership through influence, with a strong mentoring track record and ability to drive alignment across teams.
• Ability to clearly communicate complex technical concepts to senior leadership and non-engineering stakeholders and make high-impact decisions under ambiguity.
• MSc in a relevant technical field (Computer Science, AI/ML, Data Science, Mathematics, Physics, or related); PhD a plus.

Benefits

• Professional development opportunities