ANSR is hiring for one of its clients.

About ANSR MedTech:

Who We Are:

ANSR MedTech Capability Center is a new global innovation hub being established in India for a Fortune 100 Fastest-Growing Company in the MedTech sector. Built in partnership with ANSR, the center draws on ANSR's proven experience in establishing and scaling high-performance Global Capability Centers (GCCs) for leading global enterprises.

ANSR MedTech center brings together world-class engineering, product, and technology talent to build next-generation healthcare platforms and solutions that power global operations.

Our Vision:

To build a next-generation MedTech capability center that powers global healthcare innovation. We envision:

- High-impact innovation hubs shaping global product and technology roadmaps
- Centers that go beyond support functions to drive core engineering and platform development
- Sustainable, scalable ecosystems that nurture world-class MedTech talent
- Capability centers that directly influence patient outcomes worldwide.

At its core, the ANSR MedTech Capability Center is about enabling innovation that touches lives at scale.

Job Title: Performance Engineer

Department: Data Cloud S&M;

Function: CFSW

Sub-Function: Cloud

Location: Bengaluru, India

About CFSW:

Joining the Customer Facing Software (CFSW) Center of Excellence at ANSR MedTech means being part of a team that is core to delivering global, customer facing technology platforms used at scale.

You'll work on high impact systems—Salesforce, Cloud, Data Products, and Testing—that power real customer, agent, and care experiences worldwide. This is not a support or back office environment; teams are responsible for end to end execution, quality, and outcomes.

What makes this role stand out:

- Work on enterprise grade platforms that support millions of users globally
- Partner closely with senior global technology and product leaders on priorities, standards, and outcomes
- Help build a Center of Excellence from the ground up, shaping ways of working, engineering quality, and delivery excellence
- Grow as part of a Build–Operate–Transfer (BOT)journey, with increasing scope and maturity over time
- Success is measured by delivery quality, stable releases, platform value, continuous improvement, and strong collaboration with global stakeholders.

About the Role:

As the Performance Engineer – Data Cloud, you are responsible for ensuring cloud-native and AI-powered platforms meet performance, scalability, reliability, and cost-efficiency expectations. You will design and execute performance strategies across APIs,



microservices, streaming systems, data pipelines, and AI-enabled workloads. This role requires strong hands-on performance engineering depth, working knowledge of AWS, data streaming, AI-DLC, Agentic AI, and MCP-based integrations, and the ability to partner with development, SDET, architecture, and site reliability teams to scale production-grade solutions.

Key Responsibilities:

- Own performance engineering strategy, planning, execution, analysis, and reporting
- Design and execute load, stress, spike, endurance, scalability, and resiliency tests
- Build and maintain performance harnesses using tools such as JMeter, Locust, Python, Kubernetes, or equivalent
- Validate performance across APIs, microservices, streaming systems, and event-driven architecture
- Analyze performance findings and provide actionable recommendations to optimize cloud configurations, application design, and resource utilization
- Partner with development teams to identify bottlenecks early and shift performance validation left in the delivery lifecycle
- Participate in capacity planning and forecasting to support business growth and peak load scenarios
- Collaborate with site reliability engineering to refine service-level indicators, service-level objectives, monitoring, alerting, and dashboards
- Automate performance activities in CI/CD pipelines and release readiness workflows
- Document and communicate performance findings clearly to engineering teams, leadership, and stakeholders
- Ensure compliance with FDA, HIPAA, and internal quality standards
- AI, AI-DLC & Contemporary Engineering
- Support performance validation of AI-powered capabilities, including AWS Bedrock-based solutions
- Understand AI-Driven Development Lifecycle (AI-DLC) practices and how AI tools can improve engineering, testing, analysis, and documentation
- Evaluate performance characteristics of Agentic AI workflows, including latency, throughput, reliability, repeatability, and cost
- Support performance testing of MCP-based integrations and enterprise data/API access patterns, including MuleSoft MCP where applicable
- Partner with engineering teams to ensure AI-enabled features are production-ready, observable, scalable,



and cost-aware
- Use AI-assisted tools to improve performance test generation, analysis, anomaly detection, and reporting
- Performance, Scale & Observability
- Define performance baselines, thresholds, and release readiness criteria
- Create dashboards and reports using observability tools such as AWS CloudWatch, DataDog, OpenTelemetry, or equivalent
- Analyze latency, throughput, error rates, saturation, resource utilization, and cost drivers
- Validate system behavior under expected load, peak load, failure conditions, and growth scenarios
- Provide recommendations to improve resilience, scalability, and cost efficiency across cloud services
- Ensure performance risks are identified early, tracked, and clearly communicated
- Data, Streaming & Integration Quality
- Validate performance of data streaming systems such as Kafka, MSK, RabbitMQ, or equivalent
- Test real-time ingestion, transformation, and processing workflows
- Measure and analyze throughput, lag, backpressure, retry behavior, and failure recovery
- Partner with development and data engineering teams to ensure data flows are reliable, scalable, and ready for AI and analytics use cases
- Understand that AI system quality and performance depend on reliable, high-quality, well-structured data inputs.

Minimum Requirements :

- Bachelor's degree in Computer Science, Software Engineering, Electrical Engineering, or related field
- 3-5 years of performance engineering, performance testing, or reliability engineering experience
- Experience planning and designing performance tests for load, stress, spike, endurance, and scalability scenarios
- Experience developing performance test scripts for cloud or distributed systems
- Experience working with global engineering teams, preferably in a US + India delivery model
- Strong written, verbal, presentation, and stakeholder communication skills
- Experience in regulated environments such as medical device, healthcare, or life sciences is preferred.

Success Criteria:

- Clear performance baselines and release readiness criteria are established and consistently used
- Performance issues are identified earlier in the delivery lifecycle
- Cloud platforms scale reliably under expected and peak load conditions
- Performance testing is automated and integrated into CI/CD workflows
- AI-powered and Agentic AI workflows are validated for latency, scalability, reliability, and cost
- Engineering teams receive clear, actionable performance recommendations that improve production stability.

📌 Performance Engineer (Bengaluru)
🏢 ANSR
📍 Bengaluru