Lead Software Engineer

'Role Summary

As a Performance Test Engineer, you will design, implement, and execute comprehensive

performance, load, stress, and endurance testing for the AI Search Platform. You will be

responsible for ensuring the system meets stringent latency requirements (<5 seconds

streaming summaries) under peak healthcare consumer traffic. You will collaborate

closely with AI developers, cloud architects, and clinical governance SMEs to analyze

bottlenecks, measure LLM token/latency metrics, and guarantee the platform's high

availability and reliability.

Key Responsibilities

• Performance Testing Strategy: Plan, script, and execute load, stress, scalability,
  
  

and endurance tests for the conversational search, APIs, and batch ingestion

pipelines.

• Response Time Validation: Benchmark and validate that the AI Summary Engine
  
  

begins streaming responses in less than 5 seconds from query submission under

concurrent load.

• Testing Tool Execution: Utilize performance and profiling tools such as JMeter,
  
  

Artillery, Lighthouse, and Fiddler to measure end-to-end response times and UI

rendering.

• AI & LLM Evaluation: Measure LLM-specific latency, throughput, token usage, and
  
  

accuracy bottlenecks using tools like LangSmith, Judge LLM, and Virtusa's AI

Assurance Accelerators.

• Infrastructure Monitoring: Monitor server-side performance (Azure Functions,
  
  

Azure AI Search, API Management, Cosmos DB, and Redis cache) to isolate

infrastructure-level bottlenecks.

• Ingestion Pipeline Testing: Benchmark the performance of the EOD batch
  
  

ingestion pipeline (Sitefinity CMS content harvesting, text chunking, embedding

generation, and index upserts).

• CI/CD Integration: Integrate automated performance checks and regression
  
  

baselines into the deployment pipelines.

• Security & Resilience Checks: Perform basic vulnerability assessments and
  
  

performance-under-stress evaluations using tools like OWASP ZAP to ensure

edge-level resilience.

Technical Skills & Qualifications

• Experience: Minimum of 5+ years of experience in performance engineering and
  
  

quality assurance for enterprise applications, preferably in cloud-native search or

Generative AI platforms.