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.
What You'll Be Doing
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.
Nice to Haves
Experience designing or operating control-plane and data-plane services is a strong plus.
Perks and Benefits
Snowflake is about empowering enterprises to achieve their full potential.
Culture focused on impact, innovation, and collaboration.
Opportunity to work on advanced AI technologies.
Senior individual contributor role with organization-wide impact.
Chance to shape system architecture and influence product direction.