Gigaml
Software Engineer I / II
San Francisco · Mid
Sponsorship not specifiedDetected 434 days ago
Data EngineeringAgentic AI
About the role
- You'll work across the backend, from data pipelines and integrations to agent infrastructure, shipping features alongside experienced engineers who will help you grow.
- This is a role where you'll contribute to real problems from day one.
- We expect you to ramp up quickly, take ownership of your work, and operate with increasing independence as you learn the codebase.
Responsibilities
- charts and alerts in Slack, natural language queries, and expanding Atlas to manage platform resources
- Atlas: Building features for our AI assistant: charts and alerts in Slack, natural language queries, and expanding Atlas to manage platform resources
Requirements
- Have 1-3 years of professional software engineering experience
Benefits
- Competitive base + bonus + equity
- Dinner stipend
- $500/month wellness & commuter benefit (gym, fitness classes, mental health)
- Medical, dental, and vision coverage
Company info
- Voice AI startup Giga raises $61M Series A https://fortune.com/2025/11/05/voice-ai-giga-raise-61-million-customer-service-series-a/
- DoorDash and Giga Partnership https://www.linkedin.com/feed/update/urn:li:activity:7391576181009018883/
- Giga builds AI agents trusted by the largest B2C companies in the world.
- Industry leaders like DoorDash trust Giga with their most complex support and operations workflows across voice, chat, and email.
- If being a part of this resonates with you, please apply!
- We're looking for software engineers to help build the systems that power our AI agents.
- You'll contribute to projects across our stack.
- Some examples:
- Activity Stream: Log visualization with filters, timestamps, and frequency charts to give visibility into agent behavior
- Dynamic knowledge: Adding time-based knowledge (like ongoing incidents) that auto-updates from sources like status pages
Equal opportunity
- Giga is an equal opportunity employer.
This listing is sourced directly from Gigaml's careers page and normalized into a canonical job model.