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# software engineer

- **Company:** Nectar
- **Location:** Palo Alto, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Amazon Web Services, Cloud Computing, Databases, Data Infrastructure, PostgreSQL, Pulumi, Vertica, Data Pipelines
- **Published:** October 18, 2026
- **Apply:** https://startup.jobs/member-of-technical-staff-infrastructure-nectarsocial-com-8297525

## About the Role

* 5+ years of experience operating production systems as an SRE, infrastructure, or platform engineer
 * Experience scaling databases, data infrastructure, or complex production platforms under significant load
 * Hands-on expertise with cloud infrastructure (AWS or similar) and infrastructure-as-code tooling
 * Solid programming skills for building automation, tooling, and operational services
 * Comfortable operating in fast-moving startup environments with high ownership and autonomy
 * A reliability-first mindset balanced with pragmatism about velocity and cost

Bonus Points

 * Experience standing up or maturing an SRE practice at an early-stage or rapidly scaling company
 * Familiarity with our tech stack: AWS, Pulumi, Postgres, ClickHouse, Turbopuffer, or Temporal
 * Background in capacity planning, performance engineering, or cost optimization at scale

## Description

We're looking for a software engineer to own the reliability, scalability, and operational excellence of the production systems that power Nectar's platform. We run high-volume data ingestion pipelines and real-time AI agents on top of a fast-growing customer base, and we need a seasoned SRE to help us scale these systems safely and keep them running flawlessly.

As one of our first dedicated SREs, you'll have outsized impact and ownership. You'll define how we measure, operate, and harden our infrastructure -- establishing the reliability foundations that the rest of the engineering team builds on as we scale.

What You'll Be Doing

 * Own the reliability and scalability of our production systems as they handle rapidly growing volumes of social data and real-time AI workloads
 * Define and drive SLOs, SLIs, and error budgets, and build the observability, alerting, and on-call practices to support them
 * Lead incident response and blameless postmortems, then turn what we learn into systemic improvements that prevent recurrence
 * Improve performance, cost efficiency, and capacity planning across our cloud infrastructure as the platform scales
 * Harden our infrastructure-as-code, deployment, and CI/CD pipelines for resilience and repeatability
 * Partner with engineering teams to embed reliability into system design and raise the operational bar across the org