Software Engineer
Ideogram
| Company | Ideogram |
| Category | Engineering |
| Location | Toronto |
| Remote | On-site (inferred) |
| Employment | Not stated |
| Level | Not stated |
| Salary | Not stated by the employer |
| Posted | 22 Jun 2026 |
| Last verified | 30 Jul 2026 |
| Source | Employer career page (ashby) |
Description
ABOUT IDEOGRAM
Ideogram’s mission is to make world-class design accessible to everyone, multiplying human creativity. We build proprietary generative media models and AI native creative workflows, tackling unsolved challenges in graphic design. Our team includes builders with a track record of technology breakthroughs including early research in Diffusion Models, Google’s Imagen, and Imagen Video. We care about design, taste, and craft as much as research and engineering – shipping experiences that creatives actually love.
We’ve raised nearly $100M, led by Andreessen Horowitz and Index Ventures. Headquartered in Toronto with a growing team in NYC, we're scaling fast, aiming to triple over the next year. We're a flat team with a culture of high ownership, collaboration, and mentorship.
Try Ideogram at ideogram.ai http://ideogram.ai, and check out the following links to learn more about our work: Ideogram 4.0 https://ideogram.ai/models/4.0/, Enterprise https://ideogram.ai/enterprise/, and Custom Models https://ideogram.ai/features/custom-models/.
ABOUT THE ROLE
As a Software Engineer at Ideogram, you'll build the products that put generative AI directly into the hands of creators, and build the infrastructure that will allow us to accelerate model development. You'll work across the entire stack, from crafting delightful user experiences to optimizing backend systems that serve millions, with a relentless focus on shipping features that users love. We're looking for someone who combines product instinct with strong technical ownership, user empathy, and the ability to move fast in an evolving AI landscape.
WHAT WE'RE LOOKING FOR
Product & AI Mindset
- Deep curiosity about generative AI and genuine excitement about its potential to empower creators
- Ability to navigate ambiguity and turn open-ended problems into concrete technical direction
- Knowing when to add structure and when to keep things simple
- Keeping unnecessary complexity out of the system
- Bridging the gap between product intent and technical reality
- Helping others get value from AI tools without overengineering
AI-Native Software Engineer
- Experience building and shipping software with real user impact
- Comfortable working across frontend and backend systems
- Familiarity with cloud infrastructure and modern web technologies
- Can design APIs and data models that support evolving product needs
- Use AI-native engineering tools (e.g., Claude Code, Codex, or similar) to meaningfully accelerate development velocity, debugging, and codebase comprehension
Ownership & Execution
- Self-starter who takes initiative to identify opportunities and drive them to completion
- Operates with urgency. You ship incremental value and iterate based on real user feedback
- Comfortable working with minimal direction in a fast-moving environment
- Takes responsibility for outcomes, not just code, you care about whether users love what you build
Collaboration & Communication
- Can explain technical concepts to both engineers and non-technical stakeholders
- Seeks feedback, acknowledges mistakes, and learns quickly
- Pushes for quality through constructive code review and collaboration
- Bachelor's degree in Computer Science, Engineering, related field, or equivalent practical experience
OUR STACK
We primarily use React and Python. Familiarity with the following technologies is a plus, but not required:
- OpenAPI & gRPC
- Kubernetes
- Redis & Memcached
- GCP, Google Bigtable, Google BigQuery, Google Spanner, Google Pub/Sub
- Docker & Terraform
- Cloudflare
NICE TO HAVE
- Experience integrating ML models into production applications (inference, prompt engineering, fine-tuning workflows)
- Track record of shipping consumer-facing AI products or features
- Contributions to design systems, component libraries, or developer tooling
- Experience with experimentation frameworks and feature flagging
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