The Opportunity

We're looking for a Back-End Software Engineer who wants to build ambitious AI features and own them end-to-end, from idea to production.

The team is moving quickly on LLM-powered and agentic experiences, and the technical foundation of this role is back-end engineering: designing the services, protocols, and data flows that make these features reliable, fast, and scalable. At the same time, this is not a narrowly defined back-end position. The right person is comfortable moving across the stack when the product demands it—whether that means working on a client platform, a shared protocol, or the infrastructure needed to bring a feature to life.

This is a high-ownership role. You'll take on sizeable, often ambiguous problems, shape the scope, estimate the work, and make the quality, cost, and latency trade-offs that are unique to AI products. You'll ship in tight iterations, learn from real user behavior, and keep improving the experience.

The ideal person is a back-end-strong, stack-flexible builder who enjoys turning unclear problems into shipped products and can take an AI feature from concept to users with minimal hand-holding.

Superhuman's engineers and researchers have the freedom to innovate and uncover breakthroughs—and, in turn, influence our product roadmap. The complexity of our technical challenges is growing rapidly as we scale our interfaces, algorithms, and infrastructure. You can hear more from our team on our technical blog.

As a Back-End Engineer On This Team, You Will

• Build ambitious, LLM-powered and agentic AI features and own them end-to-end, from idea to production.
• Design the services, protocols, and data flows that make AI features reliable, fast, and scalable.
• Start building and pushing code in your first week and ship impactful features in your first few months.
• Build and support production services with high call rates, targeting high availability for consumer and enterprise customers.
• Take on sizeable, ambiguous problems—shaping scope, estimating work, and making the quality, cost, and latency trade-offs that are unique to AI products.
• Move across the stack when the product demands it, from a client platform to a shared protocol to the infrastructure that brings a feature to life.
• Learn how to build infrastructure as code (IaC).
• Ship in tight iterations and learn from real user behavior to keep improving the experience.
• Have the opportunity to mentor new hires and help raise the engineering bar across the team.
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Qualifications

• Has 5+ years of relevant experience in back-end development.
• Describes themselves as back-end-strong but stack-agnostic, and is comfortable working across the stack—including on client platforms or shared protocols—when the product needs it.
• Has hands-on experience building or integrating LLM-powered or agentic features (well beyond a one-off API call), with a real feel for the cost, latency, streaming, and quality/false-positive trade-offs that come with AI products.
• Is proficient in one or more of Java, Go, or Python.
• Has experience with AWS or GCP (other cloud offerings such as Azure are a plus).
• Displays excellent software engineering fundamentals, including knowledge of algorithms and data structures.
• Has experience building, deploying, and debugging production systems at scale.
• Demonstrates perseverance when faced with tough technical issues.
• Cares about the end-user experience and strives to ensure high quality.
• Collaborates effectively with cross-functional partners—product managers, designers, linguists, and engineers on other platforms—rather than shipping in isolation.
• Has a demonstrated ability to work independently with minimal guidance, proactively manages tasks and priorities across multiple projects, analyzes and executes work efficiently, and thrives in fast-paced, results-driven environments.
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