Senior Director, Performance Engineering -Infrastructure and Reliability

We are hiring a Senior Director of Performance Engineering for our Product and Technology organization — a strategic leadership role accountable for establishing performance as a competitive advantage and core product differentiator. You will define performance strategy across the entire product stack, lead the transformation toward a performance-first culture, and build a team of performance engineers who drive continuous optimization, cost efficiency and customer experience. You will partner closely with product, engineering, infrastructure, security and observability teams to embed performance excellence into how we build, ship and operate software. 

Role overview 

As Senior Director of Performance Engineering, you own the performance strategy, standards and excellence across the entire product and infrastructure landscape. You are accountable for ensuring that all customer-facing systems, APIs, infrastructure, databases, and the delivery pipeline perform at levels that meet customer expectations, enable rapid iteration, and drive cost efficiency. This spans frontend performance, API latency, backend throughput, database query optimization, container orchestration efficiency, CDN strategy, agentic AI inference performance, and real user monitoring across all product lines. 

This is a strategic leadership role that combines technical authority with broad organizational influence. You will set performance standards, establish measurement frameworks, drive performance improvements across teams, advocate for performance investment, and champion a culture where performance is considered in every architecture decision. You work closely with engineering teams, product leaders, infrastructure/cloud operations, security, observability, and the customer success organization to ensure performance translates directly to customer value and competitive advantage. 

Your mandate is to transform performance engineering from a reactive, post-hoc optimization effort into a proactive, embedded capability that is designed into products from inception. Performance is not a feature you add later — it is a fundamental quality attribute that shapes architecture, influences release velocity, reduces operational costs, improves customer experience and enables product innovation. You will lead this cultural transformation while building a high-performing team and delivering measurable business impact. 

Duties and accountabilities 

Performance strategy and standards 

• Define organization-wide performance vision, strategy and goals aligned with product strategy, customer expectations and competitive positioning. 

• Establish performance standards and SLOs (Service Level Objectives) for latency, throughput, availability and cost across all services, APIs and customer-facing systems. 

• Define performance architecture patterns, design principles and guardrails that make performant choices the easy choices for engineering teams. 

• Own performance roadmap: prioritize performance initiatives, set timelines, and communicate progress to leadership and stakeholders. 

• Ensure performance requirements are embedded in product specifications and architecture reviews from inception, not bolted on later. 

Performance measurement and intelligence 

• Establish comprehensive performance measurement frameworks, including synthetic monitoring, real user monitoring (RUM), and observability-driven performance insights. 

• Partner with the Observability team to instrument systems for performance visibility, including detailed metrics on latency percentiles, throughput, resource utilization and cost attribution. 

• Define performance dashboards and reporting that make performance status visible to engineering teams, product leaders and executives. 

• Conduct performance baselines, benchmarking and regression analysis; identify performance issues, root causes and optimization opportunities. 

• Translate performance data into actionable insights that guide architecture decisions, infrastructure investments and optimization priorities. 

Cross-stack performance optimization 

• Own end-to-end performance from frontend through APIs, backends, databases, caching layers, message queues and infrastructure. 

• Lead performance optimization initiatives across the stack: code optimization, algorithmic improvements, database query tuning, caching strategies, CDN configuration, container efficiency, cloud cost optimization. 

• Drive adoption of performance best practices: query optimization, async processing, event-driven architectures, edge caching, resource pooling, connection management. 

• Partner with infrastructure and cloud operations teams on capacity planning, resource optimization, cost attribution and cost-performance trade-offs. 

• Address performance at scale: benchmark under realistic load; identify bottlenecks under peak traffic; ensure systems scale linearly with demand. 

Agentic AI and emerging system performance 

• Own performance strategy for agentic AI systems: inference latency, throughput, cost per inference, token-per-second processing, multi-agent orchestration efficiency. 

• Establish performance guardrails for agent systems: maximum acceptable latency for customer-facing agents, cost budgets, resource constraints, concurrent request limits. 

• Partner with AI/ML and product teams to optimize agent performance: prompt optimization, caching strategies, batching, token efficiency, model selection for latency trade-offs. 

• Measure and optimize end-to-end latency for agent workflows, including LLM inference, orchestration, tool invocation, and response generation. 

Performance culture and team leadership 

• Build and lead the Performance Engineering team, including specialists in frontend performance, backend optimization, database tuning, infrastructure efficiency and observability integration. 

• Drive a performance-first culture across Product and Technology: make performance visible, celebrate improvements, hold teams accountable for performance impact of changes. 

• Mentor engineers and engineering leaders on performance thinking; embed performance expertise into product teams and platform teams. 

• Actively review high-impact designs and pull requests from a performance lens; provide technical guidance on performance trade-offs. 

• Communicate performance strategy, wins and progress to engineering leadership, product leadership and board/executive stakeholders. 

What success looks like 

• Performance is embedded in how engineering teams design systems from the start; performance is not an afterthought or later optimization phase. 

• Performance metrics are visible to all teams; teams proactively monitor and improve performance rather than waiting for performance issues to surface. 

• Product latency, throughput and cost are measurably better year-over-year; customer experience is visibly improved due to performance gains. 

• Agentic AI systems deliver sub-second to few-second latency for customer-facing agents; cost per inference is optimized and competitive. 

• Engineering teams view performance engineers as trusted partners and performance experts they consult on architecture decisions. 

• Customer satisfaction improves due to faster product, faster feature delivery (shorter build/test/release cycles due to optimized systems), and lower service costs translating to competitive pricing. 

• Performance is a competitive differentiator; customers and prospects recognize the product as fast and efficient.

Department: Research and Development
Function: Engineering
Experience Level: Mid-Senior Level