Software Engineer, Infra/Data
Sazabi · San Francisco; New York City; United States
Extracted from the posting
Builds and scales Sazabi's log ingestion and processing pipeline, including storage, indexing, and query systems for logs. Focuses on high-throughput, low-latency distributed data processing, reliability, and cost-efficiency of backend systems. Stack is TypeScript end-to-end with PostgreSQL, Temporal, Vercel AI SDK, Terraform, Kubernetes, and AWS.
What we're building
In 2026, we're on the verge of an "infinite software crisis." How will we support, maintain, and operate the explosion in application development?
Our answer is Sazabi: the AI-native observability platform for fast-moving engineering teams.
Sazabi gives teams a single place to ask questions about their production systems in plain language, automatically visualize what's happening, and get to the root cause 10x faster. No tedious instrumentation. No dashboard configuration. No alert tuning. Just answers.
We're backed by tastemakers from the world's top AI companies: Vercel, Graphite, Daytona, Browserbase, LangChain, Mastra, Replit, and more.
What you’ll do
- Build and scale our log ingestion and processing pipeline
- Design systems for high-throughput, low-latency data processing
- Own storage, indexing, and query systems for logs
- Ensure reliability, scalability, and cost-efficiency of our backend systems
- Work on distributed systems that power real-time observability
- Debug and optimize performance at every layer of the stack
What we're looking for
- Strong experience with distributed systems and data infrastructure
- Familiarity with streaming systems, databases, and large-scale data pipelines
- Deep understanding of performance tradeoffs (latency, throughput, cost)
- Ability to design systems from scratch, not just maintain them
- Comfort working close to the metal when needed
- Bonus: experience with observability platforms, logging systems, or time-series data
Our tech
Our stack is TypeScript end-to-end. We use PostgreSQL for relational data, Temporal for durable execution, and the Vercel AI SDK to orchestrate our AI agents against the latest models. At the infrastructure layer, we use Terraform, Kubernetes, and AWS.
Some of the most interesting engineering problems we grapple with are:
- AI agents at production scale
- Log processing at scale
- Multi-region data architecture
- Real-time streaming infrastructure
- Evals and reinforcement learning
- Zero-downtime deployments and fast rollbacks
What we offer
- Competitive salary and equity
- Free lunches (in-office only)
- Health, dental, and vision insurance
- Unlimited paid time off
- Paid parental leave
Learn how we think and work
Our team comes from Brex, Y Combinator, Rootly, Google, Doppel, and other top tech companies. We move fast and hold a high bar for both the product and each other.
We operate according to six values:
- Integrity. We say what we mean, do what we say, and own our mistakes.
- Urgency. We treat every week like it matters, because it does.
- Craftsmanship. We care deeply about the quality of our work.
- Service. We're here to make developers’ and our teammates’ lives easier.
- Kindness. We're direct, and we move fast, but we treat each other well.
- Fun. We genuinely enjoy working together. If you don't love what you're building and who you’re building it with, what's the point?
You can find out more about us here:
- Watch our launch video
- Read the manifesto
- Follow us on X and LinkedIn
The Sazabi philosophy
Sazabi is more than just a tool. It’s also a philosophy. We're taking a radically different approach to observability, centered on three big ideas:
- Less is more. Most observability platforms drown you in dashboards and modules that you don’t need. We believe observability needs less UI, not more. Sazabi surfaces exactly the information you need in a simple, beautiful chat interface.
- Logs are all you need. The “three pillars of observability” idea is outdated. Sazabi accepts only one kind of telemetry: logs. This simplifies the instrumentation and product experience dramatically.
- Monitoring is dead. Creating and maintaining static alerts for a fast-evolving system is a fool’s errand. The future is agentic anomaly detection: AI agents that automatically check your app for issues 24-7.
We came to these beliefs the hard way — after years of building infrastructure and responding to incidents with tools that offered plenty of bells and whistles, but no clear answers when it counted most.
If this way of thinking resonates with you, come build with us.
