Description
We're looking for a Senior Software Engineer to help build the best Managed PostgreSQL for AI workloads. The service is already in production; the mission now is to make it the obvious choice for teams running AI applications on Postgres , first-class vector search, painless migrations from RDS / Cloud SQL / self-managed clusters, and the operational quality of a mature managed database.
You will work across the stack: control plane and lifecycle automation in Go, Postgres internals and performance, migration tooling, and customer escalations.
Responsibilities:
- Develop control plane and lifecycle automation for Managed PostgreSQL , provisioning, HA, failover, backups, PITR, version upgrades, zero-downtime maintenance.
- Tune and harden PostgreSQL itself , replication, WAL, vacuum, query planner, connection pooling, extensions , and turn that into product features and sane defaults customers don't have to think about.
- Build migration tooling that gets customers off AWS RDS, Google Cloud SQL, Azure Database for PostgreSQL, and self-managed clusters with minimal downtime.
- Drive the AI-Postgres story end to end , vector search (pgvector, pgvectorscale), hybrid retrieval, integration with the wider Nebius AI Cloud stack.
- Run the service like an SRE , define SLOs, build observability, lead incident response, feed every postmortem back into the platform.
- Work directly with customers on architecture reviews, performance escalations, and production problems.
Must-haves:
- 5+ years of professional software engineering experience with significant time spent building or operating production PostgreSQL at scale.
- Strong software engineering skills in Go or another backend/systems language.
- Deep knowledge of PostgreSQL internals: MVCC, WAL, replication, vacuum, query planning, extensions, partitioning.
- Hands-on experience with the surrounding ecosystem: Patroni / Stolon / pg_auto_failover, pgBackRest / WAL-G, pgBouncer / PgCat, logical replication tooling.
- The instincts of an ex-DBA , fluent reading of EXPLAIN ANALYZE, reasoning about lock behaviour, handling database corruptions.
- Ability to write reliable code and dig into complex problems.
- Teamwork-oriented approach.
Nice-to-haves:
- Experience with pgvector and pgvectorscale , vector search at scale, index choice, recall vs. latency trade-offs.
- Background building managed-database control planes at a cloud provider.
- Experience writing Kubernetes operators (Go + controller-runtime / kubebuilder).
- Contributions to PostgreSQL itself, popular extensions, or the surrounding OSS ecosystem.
- AI/ML workload experience , RAG pipelines, embedding stores, GPU-resident workloads.
Benefits & Perks:
- Competitive compensation
- Career growth and learning opportunities
- Flexibility and ownership
- Collaborative and innovative culture
- Opportunity to work on impactful AI projects
- International environment and talented teams