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Hiring Senior/Staff AI Evaluation Engineer

  • Source: Indeed
  • Haparz
  • Remote
  • India
  • Senior

Job Description

Job Description

Role: Senior/Staff AI Evaluation Engineer
Experience: 6+ Years
Location: Remote
Mode: Hyparz Payroll

Budget: 21 LPA

About the Role

We are looking for a Senior/Staff AI Evaluation Engineer to lead the benchmarking, validation, reliability, and safety evaluation of next-generation Agentic AI platforms.

This role sits at the intersection of Quality Engineering, Software Engineering, and AI/ML. You will build automated evaluation frameworks, benchmark AI behavior, validate LLM/RAG/agentic workflows, and establish measurable quality standards for production AI systems.

What You’ll Do

  • Design and implement automated evaluation frameworks for LLM, RAG, and agent-based applications.
  • Build and maintain golden datasets, benchmark datasets, test datasets, and regression suites for AI evaluation.
  • Develop measurable evaluation criteria for accuracy, relevance, consistency, safety, reliability, and agent behavior.
  • Perform adversarial testing to identify hallucinations, prompt vulnerabilities, unsafe behavior, and edge cases.
  • Evaluate LangGraph-based and multi-agent systems at the node, state-transition, routing, and workflow levels.
  • Use LangSmith for tracing, debugging, experiments, datasets, and evaluation workflows.
  • Work extensively with LangChain and LangGraph, including sub-graphs and conditional routing.
  • Build Python-based automation for functional, regression, integration, and end-to-end AI testing.
  • Evaluate prompts, embeddings, vector search, RAG pipelines, tool calling, and agentic workflows.
  • Validate AI systems against safety, security, privacy, and Responsible AI expectations.
  • Integrate evaluation and regression testing into GitHub-based CI/CD workflows.
  • Work with AWS and Amazon Bedrock to validate AI-powered application architectures.
  • Perform API and backend validation using REST APIs, JSON, SQL, and modern application architectures.
  • Collaborate with Engineering, Product, Data, and Quality teams to investigate failures and drive improvements.
  • Take ownership of ambiguous AI quality problems and convert them into repeatable, measurable evaluation approaches.

What We’re Looking For

  • 6+ years of experience in software engineering, quality engineering, test automation, AI engineering, ML engineering, or a related technical discipline.
  • Demonstrable hands-on experience testing or evaluating LLM, NLP, ML, RAG, or agentic AI applications.
  • Strong Python development and automation experience.
  • Deep hands-on knowledge of LangChain, LangGraph, and LangSmith.
  • Experience evaluating LangGraph node execution, state transitions, conditional routing, sub-graphs, or multi-agent workflows.
  • Strong understanding of LLMs, prompt engineering, embeddings, vector databases/search, RAG, and AI agents.
  • Experience building golden datasets, benchmark datasets, or structured AI test datasets.
  • Experience with adversarial testing and AI safety evaluation.
  • Practical understanding of security, privacy, and Responsible AI evaluation.
  • Strong GitHub experience covering repositories, branching, pull requests, code reviews, and CI/CD.
  • Experience with Claude Code or comparable AI-assisted development tools.
  • Experience with AWS and Amazon Bedrock.
  • Strong REST API, JSON, and SQL knowledge.
  • Strong experience in automated, regression, integration, and end-to-end testing.
  • Excellent analytical, troubleshooting, communication, and problem-solving abilities

Work Location: Remote

Skills

  • LangGraph
  • NodeJS
  • LangChain
  • Python
  • Github
  • amazon-web-services
  • bedrock
  • JSON
  • claude-code
  • mode
  • benchmark
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