Hybrid 3 days (offices in NYC, Denver, CO and Charlotte, NC area)

Position Summary:

Judi Health is building the technology infrastructure our nation needs to deliver the healthcare we deserve — a domain where correctness is non-negotiable and latency has real-world consequences. The Architecture organization is responsible for the technical foundation the rest of the company builds on: the standards, patterns, and infrastructure primitives that engineering teams depend on to move fast and build correctly. The Performance team sits within Architecture's Core Platform function, owning the platform's ability to understand, measure, and enforce how systems behave under load.

As a Staff Engineer in Architecture, your influence extends beyond what you ship directly. The standards you set, the patterns you establish, and the decisions you document become the reference point for how system performance is measured and managed across the organization. You are building for the platform and for the teams that build on it.

Claims adjudication, prior authorization, and auxiliary data processing drive query patterns at a volume and complexity where the interaction between schema design, cluster configuration, and connection behavior determines whether the platform holds under load with acceptable performance. You will be directly response for identifying where the ceiling is, prioritizing changes that move it with minimal disruption, and driving deeper re-architecture where the problem demands it.

One of your first major initiatives will be a comprehensive diagnostic of the platform's database architecture, focused on the systems powering claims adjudication and claims processing — the most performance-sensitive workflows on the platform. This is a deeply embedded engagement; you will work directly within these domains to understand the query patterns, connection behavior, and cluster configuration shaping how the system performs under load. From there, you will establish the benchmarking frameworks and performance baselines that give the engineering organization a reproducible way to evaluate parameter changes, schema modifications, and database upgrades before they reach production.

Position Responsibilities:

In this role, you'll own the observability infrastructure that powers our engineering organization. You will:

• Apply deep Postgres expertise to diagnose production performance problems — interpreting query plans, analyzing usage patterns, and evaluating how cluster configuration and architectural decisions shape system behavior at scale — then own the path from root cause to production remediation
• Evaluate and implement cluster topology changes and drive the architectural transformations — including the migration from synchronous to asynchronous I/O patterns — that take the platform's throughput to the next order of magnitude
• Build the benchmarking and regression-detection infrastructure that gives engineering teams a database performance signal in CI, before changes reach production
• Define and own performance contracts for the database layer: latency targets, throughput expectations, and the SLA boundaries that upstream services build against
• Lead query and schema reviews for high-risk changes; own incident response for performance-related degradations and drive post-incident findings into durable engineering improvements
• Mentor and develop senior engineers on Postgres internals, query analysis, execution plan interpretation, and the performance implications of schema decisions at scale
• Participate in a 24/7 on-call rotation to provide continuous operational support and rapid incident response

Required Qualifications:

• 10+ years of production engineering experience, with deep specialization in PostgreSQL performance and transactional systems at scale
• Deep fluency in PostgreSQL internals: MVCC, autovacuum behavior, query planner statistics, locking semantics, and the interaction between transaction patterns and long-running queries
• Demonstrated ability to diagnose and remediate production database performance problems in regulated or correctness-critical environments — WAL write amplification, buffer pool cache pressure, reader/writer usage constraints from replica lag, and the failure modes sharding and partitioning introduce at scale — where performance improvements cannot compromise data integrity
• Experience designing and building performance benchmarking and regression-detection systems — including CI-integrated performance gates and observability pipelines — that give engineering teams pre-production visibility into database performance across the stack, not just the database layer
• Experience evaluating and implementing cluster topology changes: connection pooling configuration, read replica strategy, sharding approaches, and PostgreSQL parameter tuning for high-concurrency transactional workloads
• A track record of influencing database performance standards and architectural decisions across teams — driving decisions through influence, without direct authority, and producing documentation that holds up over time
• Strong written and verbal communication — you produce performance standards and architectural guidance that the broader engineering organization depends on
• Comfortable operating with ambiguity — at this level, you will be handed problems, not plans, and are expected to identify the right approach and drive it from first principles to production
• Strong experience supporting 24/7 production on-call rotations, including responding to alerts and resolving incidents outside of standard business hours

Preferred Qualifications:

• Direct experience with Aurora PostgreSQL at scale — including familiarity with the operational constraints of a managed PostgreSQL deployment: connection limits, storage autoscaling behavior, I/O throughput ceilings, and the performance characteristics of Aurora's distributed storage layer
• Hands-on experience with connection pooling middleware — particularly the operational tradeoffs between pooling modes (session, transaction, statement) in high-concurrency transactional workloads; e.g. PgBouncer, PgDog, or equivalent
• Experience with asynchronous Python I/O patterns (asyncio, asyncpg, or equivalent) and the architectural migration from synchronous to asynchronous database interaction
• Familiarity with horizontal scale strategies for transactional PostgreSQL workloads — including logical and physical sharding approaches and the tradeoffs they introduce for data model complexity and query routing
• Familiarity with the boundary between OLTP and OLAP workloads — and the ability to recognize when analytical query patterns are better served by a purpose-built system than optimized on the transactional cluster
• Systems-level programming experience in Rust, Go, or C/C++ — while the primary focus of this role is database optimization, you'll be actively involved in application development, and the ability to work at lower levels of the stack when performance demands it is a meaningful advantage
• Background in pharmacy benefit management, claims adjudication, healthcare data systems, or other regulated, correctness-first transactional environments

Nothing in this position description restricts management’s right to assign or reassign duties and responsibilities to this job at any time.