Software Engineer (SWE/SWE II), AI Platform - Slack
AI Infrastructure
About the Role
About Slack AI
The team's mission involves transforming how people work by making Slack an AI-powered operating system. Engineers focus on challenges like unlocking knowledge and reducing noise while building consumer-grade AI experiences within existing workflows.
About the Team
The AI and ML Infrastructure team operates within Slack's Core Infrastructure organization, handling foundational systems for machine learning and AI. They design platforms supporting the complete ML lifecycle — from training through monitoring — and are evolving toward large-scale, distributed model systems.
Core Focus Areas
- ML Infrastructure: Low-level systems powering training and inference at scale, including distributed systems using Kubernetes, GPU infrastructure, and open-source ML stacks such as KubeRay and vLLM.
- AI Platform: Developer-facing tools, SDKs, and workflows enabling product teams to integrate AI efficiently and safely, serving as a connective layer between core infrastructure and product engineering.
About the Role
The position involves building developer experience and tooling that powers AI at Slack. Engineers treat internal engineers as primary customers, designing SDKs, evaluation frameworks, and infrastructure enabling faster, more reliable AI feature shipping.
Key Responsibilities
- Drive evolution toward self-service, developer-friendly AI/ML platform environments.
- Build and maintain SDKs, feature generation tools, and CI/CD pipelines.
- Manage integrations with managed AI services across multiple cloud providers.
- Design and operate AI quality evaluation frameworks and prompt engineering infrastructure.
- Collaborate with ML modeling, AI quality, and product engineering teams.
- Build production-grade software using modern engineering practices with AI as a core component.
- Design systems where AI agents integrate seamlessly into human workflows.
- Contribute to shared system context repositories.
- Evaluate code (human or AI-generated) for correctness, quality, security, and performance.
Required Qualifications
- Experience building developer tooling, libraries, or CI/CD pipelines.
- Experience operationalizing Large Language Models and building integrations with cloud provider APIs (AWS, GCP, Azure).
- Experience with AI quality evaluation frameworks or prompt engineering infrastructure.
- Strong proficiency in Python, PHP, or Hacklang.
- Infrastructure as code experience and modern software engineering practices.
- Strong communication skills for technical concepts.
- Familiarity with unit testing, code review, design documentation, and debugging methodologies.
- Curiosity and determination to troubleshoot issues.
- Ability to work collaboratively on complex projects with diverse teams.
- Related technical degree (required).
- Demonstrated AI-first engineering approach.
- Advanced prompt engineering skills.
Locations: Seattle, WA / Austin, TX / Atlanta, GA / Bellevue, WA.
Compensation: $117,200 - $223,900 USD annually (base), plus bonuses, equity, and benefits.
