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.
