Staff 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
• 8+ 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 Staff 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