Applied AI (Performance Testing Engineer)

Skill : APPLIED AI PLATFORM ENG. (PERFORMANCE ENGINEER)

Level : Assistant Manager /Manager

Experience : Assistant Manager(6-9 Yrs) /Manager(10-13 Yrs)

Work location: Assistant Manager(Hyderabad/Bangalore ) /Manager(Hyderabad)

Mode of Interview : virtual

Work Model-Hybrid (3 days work from office / 2 days work from home )

Primary Skills : Performance Testing+Performance Engineer+(Loadrunner/K6)+Monitoring tools +Cloud +AI (ChatGPT, Claude, Gemini, Copilot)

Required Qualifications:

• A bachelors degree in computer science, software engineering, data science, machine learning, or related discipline. Experience is the most relevant factor. Hands On experience with Performance Engineering is important.
• 10+ years of software and platform engineering experience with most of the following: Angular, React, NodeJS, Python(Mandatory), , C#, .NET, Java, Rust, SQL/NoSQL, PyTorch, TensorFlow, LangChain, LangGraph, LangSmith, LangFuse, Terraform, as well as unit, integration, and end-to-end testing frameworks & tools, specifically BDD, Gherkin, Cucumber, Playwright, and Selenium.
• 3+ years of experience designing, building, and operating AI/ML platform or infrastructure, with hands-on experience across building tooling for MLOps/LLMOps, model serving, retrieval and vector infrastructure, and eval/observability instrumentation for LLM integration (OpenAI, Anthropic, or open-source models).
• 3+ years of experience with cloud-native engineering on any of the cloud hyperscalers such as Azure, AWS, or GCPincluding their AI/ML services such as Azure OpenAI, AWS Bedrock, or Vertex AI—as well as container orchestration (Kubernetes, Docker), Big Data, Databricks, CI/CD at platform scale, and distributed systems.
• 1+ years of experience establishing engineering standards and golden paths, including actively leading, mentoring, and guiding team members in the adoption and continuous improvement of these standards, treating the platform as a product.
• Prior experience with AI control-plane and agent-runtime patterns: model/LLM gateway, A2A and MCP integration, agent runtimes (e.g., Google ADK, Amazon Bedrock AgentCore), guardrails (PII redaction, prompt-injection, content, tool permissioning/tool-RBAC), policy-as-code, and multi-tenant isolation.
• Prior experience with enterprise data platform engineering: data pipelines, self-service and data-product enablement, governance-as-code enforcement, and metadata/lineage.
• Prior software engineering experience with the understanding of Business Context Diagrams (BCD), sequence/activity/state/entity relationship/data flow diagrams, OOP/OOD, data structures, algorithms, and code instrumentations, and AI-augmented spec-driven development.
• Prior experience using methodologies & tools such as XP, Lean, DevSecOps, SRE, ADO, GitHub, SonarQube, and ArgoCD to deliver high-quality platforms and products rapidly.