Job Description

Position Overview

The Director of Platform & Performance Engineering is a hands-on technical leader responsible for accelerating the scalability, performance, and operational resilience of our backend SaaS platform services. As a leader in the AI-driven CLM space, we are rapidly expanding product capabilities and customer scale — and this role ensures our backend platform not only keeps pace but enables that growth.

Reporting directly to the Chief Technology Officer, this leader will build and lead a strong, accountable backend engineering team focused on improving and evolving the technical foundation and performance of our core platform and data services.

This role works closely with application engineering, Cloud Operations, and Product leadership to ensure platform investments directly accelerate product velocity, customer value, and innovation.

This is a deeply technical player–coach role requiring strong hands-on expertise in backend services, distributed architectures, database performance engineering, and production-scale troubleshooting.

Mission of the Role

Build and lead a high-performing Core Platform Engineering team that:

Rapidly improves scalability, reliability, and observability of the core backend platform

Establishes systematic load testing, regression detection, and performance benchmarking practices

Drives measurable reductions in latency, error rates, and infrastructure cost per transaction

Leverages modern tooling, including AI-assisted analysis, to accelerate bottleneck identification and remediation

Partners closely with application engineering and Cloud Operations to ensure platform stability under real-world production load

Job Responsibilities

Platform Strategy & Roadmap

Own and drive the performance, scalability, and reliability roadmap for the backend platform in close partnership with the CTO and engineering leaders, ensuring the platform scales with aggressive product and customer growth.

Prioritize performance and stability investments while balancing near-term delivery commitments.

Performance & Scalability Engineering

Establish practical performance engineering practices, including load testing, benchmarking, and regression detection.

Proactively identify and eliminate performance bottlenecks to ensure fast, responsive user experiences at scale.

Design and execute realistic production-scale load testing scenarios that mirror customer behavior.

Establish performance regression gates in CI/CD pipelines.

Drive systematic root-cause analysis of production performance incidents.

Quantify and publish performance baselines and improvement targets.

Establish performance baselines and drive measurable improvements in throughput, latency, and resource efficiency.

Backend & Database Engineering

Drive excellence in relational database architecture across MySQL and PostgreSQL environments in AWS (RDS/Aurora).

Lead database optimization strategies, indexing improvements, and schema evolution practices.

Partner with Cloud Operations to align infrastructure and data-layer scaling strategies.

Improve transactional integrity, concurrency handling, and data reliability at scale.

Lead query optimization initiatives based on real production workload analysis.

Identify and resolve lock contention, connection pool saturation, and concurrency bottlenecks.

Partner with Cloud Operations to right-size database infrastructure based on performance data.

Observability & Runtime Intelligence

Strengthen metrics instrumentation, structured logging and tracing across backend services.

Partner with SRE and Cloud Operations to enhance diagnostic capabilities and operational transparency.

Define measurable performance and reliability KPIs.

Ensure comprehensive instrumentation across critical backend paths.

Correlate load testing results with runtime metrics and tracing data.

Improve mean time to detect (MTTD) and mean time to resolve (MTTR) for performance incidents.

Hands-On Technical Leadership

Engage directly in cross-team architectural design reviews, complex system decisions, and strategic refactoring initiatives.

Provide technical mentorship and elevate backend engineering standards.

Balance strategic direction-setting with practical, hands-on execution where needed.

Serve as a senior escalation point for complex backend performance or architectural challenges.

Clarify backend platform ownership boundaries in partnership with Product Engineering and Cloud Operations.

Organizational Leadership

Recruit and develop a team of strong backend, database, and platform engineers.

Set clear expectations for engineering rigor, delivery accountability, and code quality.

Foster a culture of accountability, speed, craftsmanship, and continuous improvement.

Partner effectively with Product Engineering and Cloud Operations to ensure cohesive platform evolution.

Build a strong team capable of independently owning critical platform domains.

Influence engineering standards and platform practices across multiple application teams through collaboration and technical leadership.

Other duties as assigned

Required Qualifications

12+ years of backend engineering experience, including senior technical leadership roles.

Deep hands-on expertise with Java (JEE, Spring, or comparable enterprise frameworks).

Strong proficiency in Python for tooling, automation, or services development.

Strong understanding of distributed systems, concurrency, and scalable SaaS architectures

Experience designing and implementing load tests.

Experience using performance, observability, and scalability testing tools (Grafana, Jmeter, query EXPLAIN/ANALYZE, OpenTelemetry).

Strong expertise in performance optimization of relational database access patterns, including MySQL and PostgreSQL.

Experience evolving large-scale applications toward modular or microservices-based architectures.

Familiarity with containerization technologies (Docker, Kubernetes).

Experience using modern engineering tools, including AI-assisted development tools, to improve productivity and code quality.

Ability to apply AI tools pragmatically while maintaining architectural integrity and engineering standards.

Demonstrated ability to collaborate effectively across engineering, infrastructure, and product organizations.

Preferred Qualifications

Experience supporting enterprise SaaS platforms at significant scale.

Familiarity with performance tuning and profiling tools.

Experience implementing distributed tracing frameworks.

Experience partnering closely with infrastructure and SRE teams in AWS environments.

Background in enterprise workflow or data-intensive platforms.

Experience designing reusable platform services or shared data infrastructure within a growing SaaS environment.

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