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Home/Jobs/Applied AI Platform Engineer – Performance Engineering
Applied AI Platform Engineer – Performance Engineering
Big 4 Organization
Hyderabad / Bengaluru
6-13 years
1 day ago
$47.0K–75.9K/yr
Full-time
Hybrid
Skills Required LLMOps
Gen AI
ChatGPT
Claude
Gemini
Retrieval
Azure OpenAI
LangChain
AI/ML
MLOps
Performance Engineering
Performance Testing
LoadRunner
K6
Python
Description Applied AI Platform Engineer roles focused on performance engineering, AI/GenAI, and cloud platforms for a leading Big 4 organization.
Company: leading Big 4 organization
Role: Applied AI Platform Engineer – Performance Engineering
Location: Hyderabad / Bangalore | Hyderabad | Hybrid – 3 Days WFO / 2 Days WFH
Experience
- Assistant Manager: 6–9 years
- Manager: 10–13 years
- Solid Performance Engineering experience
- Python hands-on experience mandatory
- Manager-level team leadership experience
- Experience establishing engineering standards and golden paths
- Experience mentoring engineers
- Experience building scalable AI/ML platforms
Responsibilities
- Combine software and platform engineering with modern AI/ML infrastructure and GenAI capabilities
- Build and support AI/ML platforms
- Work on performance engineering and testing
- Work across AI/ML and GenAI platform components
- Work with model serving, retrieval, vector infrastructure, evaluation, and observability
- Work with cloud platforms and managed AI services
- Work with Kubernetes, Docker, Databricks, and distributed systems
- Use Terraform, CI/CD, and infrastructure as code
- Use OpenTelemetry and monitoring
- Support DevSecOps and SRE practices
- Work on AI control plane and agent runtime
- Support MCP and A2A integration
- Apply policy-as-code and AI guardrails
Additional Responsibilities
- Interview process is virtual
- Travel up to 10% based on business requirements
Nice To Have
- Hands-on AI tools such as ChatGPT, Claude, Gemini, and Copilot
- Azure OpenAI
- AWS Bedrock
- Vertex AI
- LangChain
- LangGraph
- LangSmith
- LangFuse
More Skills Monitoring Tools, Cloud, AI/GenAI, Copilot, GenAI Platforms, Model Serving, Vector Infrastructure, AI Evaluation, Observability, Azure, AWS, GCP, AWS Bedrock, Vertex AI, Kubernetes, Docker, Databricks, Distributed Systems, Terraform, CI/CD, Infrastructure as Code, LangGraph, LangSmith, LangFuse, OpenTelemetry, DevSecOps, SRE, AI Control Plane, Agent Runtime, MCP, A2A Integration, Policy-as-Code, AI Guardrails
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