Performance Engineer Lead / Architect

About Impact Analytics

Impact Analytics™ (Series D Funded) delivers AI-native SaaS solutions and consulting services that help companies maximize profitability and customer satisfaction through deeper data insights and predictive analytics.

With a fully integrated, end-to-end platform for planning, forecasting, merchandising, pricing, and promotions, Impact Analytics empowers companies to make smarter decisions based on real-time insights rather than relying on last year's inputs to forecast and plan this year's business.

Powered by over one million machine learning models, Impact Analytics has been leading AI innovation for a decade, setting new benchmarks in forecasting, planning, and operational excellence across the retail, grocery, manufacturing, and CPG sectors.

In 2025, Impact Analytics is at the forefront of the Agentic AI revolution, delivering autonomous solutions that enable businesses to adapt in real time, optimize operations, and drive profitability without manual intervention.

Website: www.impactanalytics.co

Impact Analytics builds AI-powered, Cloud-Native products and platforms. As we tackle increasingly complex backend challenges, we are looking for seasoned backend architects to collaborate with product and engineering teams in shaping the future of enterprise software.

About The Role

At Impact Analytics, we are redefining how enterprise SaaS platforms scale in the age of AI. Performance is no longer a one-time activity—it's a continuous engineering discipline.

As a Performance Engineer, you will operate at the intersection of systems thinking, observability, and AI-augmented development. You'll play a critical role in ensuring our platform delivers high performance at scale while leveraging modern AI tools to accelerate analysis and decision-making.

What Lands You In This Role

• Own the end-to-end performance engineering strategy for the platform, including benchmarking, workload modelling, capacity planning, and scalability testing.
• Define performance SLAs/SLOs, latency budgets, throughput targets, and reliability guardrails for critical services and user journeys.
• Design, build, and maintain performance test frameworks for APIs, microservices, UI workflows, asynchronous jobs, batch workloads, and data-intensive pipelines.
• Lead load, stress, endurance, spike, failover, and capacity testing across distributed systems.
• Identify bottlenecks using Observability tools and AI assisted workflows across application code, databases, caching layers, queues, network paths, containers, and orchestration platforms.
• Drive root-cause analysis for performance regressions and production incidents, and partner with engineering teams to implement durable fixes.
• Establish performance gates in CI/CD so regressions are detected before release.
• Build observability standards using metrics, logs, traces, profiling, and dashboards to measure system health and performance trends.
• Collaborate with security and architecture teams to ensure performance engineering aligns with enterprise-grade reliability, compliance, and resilience expectations.
• Mentor engineers and QA teams on performance best practices and create a culture of proactive, measurable engineering quality.
• Publish performance review reports and communicate findings, risks, and recommendations to engineering leadership and stakeholders.
  
  

Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• 8+ years of experience in software engineering, platform engineering, SRE, or performance engineering, with at least 2+ years in a lead role.
• Proven hands-on expertise in performance testing and tuning for large-scale SaaS or cloud-native distributed systems.
• Strong experience with tools such as JMeter, Gatling, k6, Locust, LoadRunner, or equivalent frameworks.
• Deep understanding of system internals including CPU, memory, disk I/O, networking, concurrency, threading, garbage collection, and caching.
• Strong knowledge of microservices, REST/gRPC APIs, event-driven systems, and containerized workloads.
• Experience tuning SQL/NoSQL databases, queries, indexing strategies, and high-volume data access patterns.
• Experience with observability and APM tools such as Prometheus, Grafana, Datadog, New Relic, OpenTelemetry, Elastic, or similar.
• Strong coding/scripting skills in at least one modern language such as Python, Java, Go, JavaScript/TypeScript, or Rust.
• Solid experience with cloud platforms (GCP preferred) and modern CI/CD pipelines.
  
  

Preferred Qualifications

• Experience working on AI/ML, analytics, optimization, forecasting, or data platform workloads.
• Experience with multi-tenant enterprise SaaS products handling large data volumes and complex customer configurations.
• Knowledge of cloud cost optimization and performance-efficiency trade offs.
• Experience mentoring teams and building a repeatable performance engineering practice across multiple product lines.
  
  

What We Offer

• An opportunity to be part of some of the best enterprise SaaS products to be built out India
• Opportunities to quench your thirst for problem-solving, experimenting, learning, and implementing innovative solutions
• A flat, collegial work environment, with a work hard, play hard attitude
• A platform for rapid growth if you are willing to try new things without fear of failure.
• Remuneration with best-in-class industry standards with generous health insurance cover.
  
  

Some of our accolades include

• Ranked as one of America's Fastest-Growing Companies by Financial Times for five consecutive years: 2020-2024.
• Ranked as one of America's Fastest-Growing Private Companies by Inc. 5000 for seven consecutive years: 2018-2024.
• Voted #1 by more than 300 retailers worldwide in the RIS Software LeaderBoard 2024 report.
• Ranked #72 in America's Most Innovative Companies list in 2023—by Fortune—alongside companies like Microsoft, Tesla, Apple, IBM, etc.
• Forged a strategic partnership with Google to equip retailers with cutting-edge generative AI tools.
• Recognized in multiple Gartner reports, including Market Guides and Hype Cycle, spanning assortments, merchandising, forecasting, algorithmic retailing, and Unified Price, Promotion, and Markdown Optimization Applications.