Principal Software Engineer, Snorkel AI

• This is a role for someone who wants to operate at the nexus of distributed systems, LLM infrastructure, synthetic data, and agentic orchestration
• Bachelor’s degree in Computer Science or related field
• 12+ years of experience building customer-facing, cloud-native software systems
• Deep experience with AI/ML pipelines, LLM-based systems, or agentic workflows
• Experience with distributed computing, large-scale data systems, or orchestration frameworks
• Experience at high-growth technology startups
• Experience building software products for large enterprise customers
• Expertise in Python and cloud platforms (AWS, GCP, or Azure)
• Strong understanding of production web-scale systems: monitoring, telemetry, reliability, performance, debugging, and triage
• Passion for mentorship, technical leadership, and elevating engineering cultur

Desirable

• We are looking for a Principal Software Engineer to define and drive the technical direction of our AI Platform
• Architect the core platform that powers synthetic data generation, agentic workflows, RL environments, and scalable LLM operations
• Build distributed systems that allow customers — and our own expert network — to generate datasets and evaluations at unprecedented scale
• Design and evolve the APIs, compute services, and orchestration layers that empower internal and customer-facing applications
• Collaborate across product, research, and engineering teams to define the long-term technical strategy of Snorkel
• Act as a technical leader, mentor, and culture-setter for the engineering organization
• Serve as a key advisor to company leadership while owning high-impact, highly ambiguous problem spaces
• Think years ahead about where AI is going — and help Snorkel build the infrastructure that gets us there
• There is intentionally no narrow focus for this role. You will work across the stack, across teams, and across disciplines. You should be excited to take on the most complex and impactful engineering challenges in the company
• Today, our AI Platform team builds the scalable architecture that powers this mission. We develop the systems that allow global organizations to:
• Generate and refine synthetic data at massive scale
• Create and evaluate agentic systems that reason, act, and improve over time
• Provision RL training environments and simulation frameworks for next-generation AI agents
• Deploy robust benchmarks, datasets, and automated labeling pipelines to accelerate model development
• Run LLMs and multi-agent systems efficiently, reliably, and cost-effectively across cloud and hybrid environments
• Our platform enables an ecosystem of expert contributors to create the datasets and evaluation environments that frontier models rely on to improve
• We combine a decade of academic research with production-grade engineering to help customers build differentiated, high-performance AI systems faster than ever before