Job Description Summary: Senior Software Architect 2, Performance Engineering

Company: ModMed

About the Role

We are seeking a high-impact, strategic Senior Architect, Performance Engineering to drive the technical vision, process frameworks, and execution roadmap for our enterprise-wide performance engineering platform.

In this role, you will champion a proactive, shift-left engineering philosophy that moves far beyond traditional late-stage, reactive load testing. You will be responsible for architecting the blueprints for a developer-centric, self-service testing ecosystem, designing sophisticated data management strategies, and embedding real-time performance analytics directly into continuous integration and deployment (CI/CD) pipelines across decentralized product lines.

As a Senior Architect, you will establish the organizational processes required to elevate our high-scale, sharded multi-tenant architectures into fully automated, metrics-driven performance gates. Simultaneously, you will define the enablement model to embed advanced performance engineering and optimization standards by default into the development lifecycles of our greenfield AI product initiatives.

This role requires an elite engineering baseline combining advanced protocol-level performance modeling, deep multi-layer application profiling, complex relational database diagnostics, and automated data privacy governance.

Core Responsibilities

1. Performance Architecture Platform Blueprinting

- Config-Driven Ecosystem Design: Design, build, and maintain a highly reusable, protocol-abstract, and developer-centric performance automation framework using containerized load-generation technologies (e.g., Gatling, Locust).

- Multi-Layer Runtime Diagnostics: Architect deep-dive, continuous profiling strategies that isolate regressions across the application layer (monitoring JVM garbage collection intervals, memory leak vectors, heap usage peaks,



and thread pool exhaustions) alongside the infrastructure storage layer.

- Telemetry Systems Optimization: Define and deploy asynchronous metric collection pipelines and distributed tracing matrices (e.g., OpenTelemetry, Jaeger) to aggregate real-time system performance and context across multi-service boundary lines into unified monitoring dashboards.

2. Automated Process Design Shift-Left Release Gates

- Shift-Left Pipeline Integration: Standardize and execute the performance review lifecycle, enabling product squads to define load parameters via version-controlled definitions (.perf.yaml) directly inside their code repositories.

- Automated Pipeline Gates: Automate validation hooks to track code-level performance metrics within pull requests, establishing automated status checks that block expensive, unindexed queries or excessive sequential database calls (10+ DB calls per operation) before code merges to main.

- Performance Tiering SLAs: Standardize uniform Service Level Agreements across engineering groups, splitting endpoints into predefined latency tiers (e.g., Level 1 synchronous operations under 100 ms; Level 2 business transactions 200 ms to 500 ms).

3. Data Engineering Compliance Governance

- Relational Seeding Data Redaction: Design automated utilities for relational data masking, anonymization, and synthetic data seeding. Ensure compliance-regulated datasets are securely de-identified (HIPAA/PII compliant) while perfectly maintaining production-scale relational volume and multi-tenant index depths.

- Workload Scenario Modeling:



Formulate advanced architectural workload models that accurately replicate real-world multi-tenancy, high-concurrency loops, and complex system traffic without requiring a perfectly mirrored production setting.

4. Greenfield AI Cross-Product Enablement

- Self-Service Onboarding Framework: Drive the plug-and-play reusability model allowing decentralized product teams (EMA, Klara AI, RCM AI) to seamlessly inherit core engine libraries, drop in localized application specifications, and run high-concurrency traffic loops independently.

- AI-DLC Optimization: Provide specialized configuration blocks to track metrics unique to AI workloads, such as application-layer model inference latency, GPU/CPU token generation thresholds, and parallel processing capabilities under peak load.

5. Technical Leadership Process Mentorship

- Enterprise Process Ownership: Act as a strategic force multiplier across the engineering ecosystem, defining, publishing, and driving the organizational processes for performance engineering hygiene.

- Cross-Team Mentorship: Serve as the preeminent subject matter expert across the organization, directing high-impact cross-functional initiatives, influencing technology roadmaps, and mentoring senior engineers, SDETs, and development leads on tracing, profiling, and mitigating systemic bottlenecks.

Required Skills Experience

- Performance Engineering Tenure: 14+ years of professional software engineering and quality assurance experience, with a definitive, proven track record of architecting distributed performance testing platforms and leading organizational process changes.

Disclaimer : This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 Senior Software Architect 2 (Telangana)
🏢 ModMed Technologies India Private
📍 Telangana