Senior Software Engineer - Observe by Snowflake, AI Products

Snowflake2 months ago

Location

US-CA-Menlo Park

Type

Full Time

Salary

USD 200,000 – 287,500

Level

Senior

Role

Senior Software Engineer

Posted

Apr 29, 2026

Full TimeSenior

The role

Summary

Join Snowflake's AI Platform team at Observe to build cutting-edge AI-powered observability products that help enterprise engineering teams resolve production issues 10x faster. As a Senior Software Engineer on the AI Products team, you'll own full-stack features end-to-end, architecting and shipping customer-facing AI products including the flagship AI SRE agent, Slack integrations, CLI tooling, and Model Context Protocol capabilities. This role demands strong TypeScript proficiency, full-stack web development expertise, hands-on experience with agentic AI systems, and a product-first mindset to deliver exceptional user experiences at scale.

What you'll do

Full-Stack Feature Ownership: Own features end-to-end from API design and backend logic through frontend implementation, shipping production-ready AI products with velocity and quality while maintaining high engineering standards

AI SRE Product Development: Build and evolve Observe's flagship AI SRE product that enables engineering teams to resolve production incidents up to 10x faster through intelligent signal correlation and root cause analysis

Real-time Integration Development: Develop AI SRE Slack integrations that surface real-time agentic capabilities directly within team workflows, enabling seamless interaction with AI agents in existing communication platforms

Developer Tooling & CLI Systems: Design and implement developer-facing CLI tools, backend APIs, and agent-first command-line interfaces that empower engineering teams and improve operational efficiency across organizations

Model Context Protocol Expansion: Extend Observe's Model Context Protocol integrations to enhance agentic AI system capabilities and extend the platform's reach across enterprise environments

API Design & Integration: Design robust RESTful APIs and confidently consume third-party APIs, functioning as both a producer and consumer in a fast-moving, interconnected architecture

Cross-Functional Collaboration: Partner closely with product managers and design teams to ensure features balance exceptional user experience with technical excellence and maintainability

Evaluation & Quality Assurance: Develop evaluation pipelines and testing frameworks that ensure model performance, system quality, and production readiness for AI-powered features

What we look for

Technical

TypeScript ProficiencyExpert-level TypeScript skills required; core language for all feature development across the full stack

Full-Stack Web DevelopmentDemonstrated proficiency building full-stack web applications with solid understanding of backend logic, API design patterns, database interactions, and frontend user interfaces

Node.js Backend FrameworksProduction experience with server-side Node.js frameworks such as Express.js, Hono, Fastify, or equivalent frameworks for building scalable APIs and services

Agentic AI Systems & Tool-Use PatternsHands-on experience building or integrating agentic AI systems and implementing tool-use patterns with SDKs including Vercel AI SDK, Anthropic SDK, LangGraph, or Tanstack AI SDK

Model Context Protocol ImplementationExperience implementing and deploying MCP servers over HTTP, extending AI agent capabilities through standardized protocol implementations

Agent-First CLI DevelopmentExperience building agent-first CLI systems using Node.js or Bun runtime environments with sophisticated user interaction patterns

RESTful API Design & ConsumptionStrong capability in designing clean RESTful APIs and consuming third-party APIs with proper error handling, authentication, and integration patterns

Education

Bachelor's Degree in Computer Science or EngineeringBS/MS in Computer Science, Engineering, or equivalent professional experience demonstrating advanced software engineering capabilities and architectural thinking

Experience

Production Full-Stack DevelopmentMinimum 5+ years of professional software engineering experience building and shipping production full-stack applications with ownership across multiple technology layers

AI/ML Product DevelopmentDirect experience architecting and deploying AI-powered features in production environments, working with LLMs, evaluation pipelines, and agentic systems at scale

Fast-Paced Environment NavigationProven ability to move quickly in rapidly evolving codebases and environments while maintaining code quality, maintainability, and technical standards

Developer Experience FocusTrack record of building developer tooling, internal platforms, or productivity infrastructure that demonstrably improved team efficiency or engineering velocity

Skills

Required skills

TypeScriptCore programming language requirement for end-to-end full-stack development

Full-Stack Web DevelopmentComplete capability across backend APIs, frontend interfaces, and database interactions

Node.js FrameworksProduction experience with Express.js, Hono, or similar server-side frameworks

Agentic AI System DevelopmentBuilding and integrating intelligent agents using modern AI SDKs and frameworks

Model Context ProtocolImplementing MCP servers and extending AI capabilities through standardized protocols

Product ThinkingUser experience focus and ability to make implementation decisions based on product requirements

Rapid Development & QualityBalancing development velocity with code quality and architectural maintainability

Nice to have

LLM & Production Eval PipelinesHands-on experience working with Large Language Models, agents, and evaluation frameworks in production environments

Bun RuntimeExperience with Bun as a Node.js alternative runtime for enhanced performance

Developer Tooling & InfrastructurePrior contributions to developer tools, internal platforms, or productivity infrastructure that shaped team operations

Open-Source ContributionsActive contributions to open-source projects in AI, developer tooling, or observability ecosystems

Observability Ecosystem KnowledgeFamiliarity with Observe platform or broader observability concepts including logs, metrics, traces, and APM

Slack Integration DevelopmentExperience building real-time integrations and bots within Slack's ecosystem

Event-Driven ArchitectureExpertise in designing and implementing event-driven systems for real-time data processing

Compensation & benefits

Salary

USD 200,000 – 287,500 (annual)

Stock options

Available

Benefits

Comprehensive Health Insurance

Medical, dental, and vision coverage for employee and family members with competitive plan options

Retirement Planning

401(k) matching program to support long-term financial planning and retirement savings

Paid Time Off & Flexibility

Generous vacation, sick leave, and flexible work arrangements to maintain work-life balance

Professional Development

Learning stipend, conference attendance opportunities, and access to technical training programs

Stock Options & Equity

Competitive equity grants as part of overall compensation package

Remote Work Opportunities

Flexible hybrid or remote work arrangements supporting distributed teams

Startup Culture with Enterprise Scale

Maintain startup-style ownership and velocity while leveraging Snowflake's global resources, operational excellence, and ecosystem

Interview process

1
Initial Screening — Recruiter phone screen to assess background, experience with agentic AI systems, and alignment with role requirements
2
Technical Assessment — Coding interview focused on TypeScript proficiency, full-stack web development patterns, API design thinking, and problem-solving approach
3
AI Products Deep Dive — Technical discussion with AI Platform team engineers covering agentic system architecture, Model Context Protocol implementation, and production AI/ML considerations
4
Product Thinking Interview — Conversation with product managers and designers exploring how you approach user experience, prioritize features, and balance technical decisions with product goals
5
System Design & Architecture — Discussion of large-scale system design for observability platform features, focusing on scalability, reliability, and integration patterns
6
Leadership & Culture Fit — Final round with engineering leadership assessing cross-functional collaboration, growth mindset, and alignment with Snowflake's agentic enterprise vision