Junior Software Engineer developing software for demodulation and decoding of radio signals. Collaborating with a team on projects using C++ and Python.
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
Job title
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Degree requirement
Tech skills
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