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Ai Evaluations Engineer

  • Ai Evaluations Engineer job type Posted on: Oct 13, 2026
  • Ai Evaluations Engineer experience level VeeRteq Solutions Inc
  • Ai Evaluations Engineer employment type New York, New York
  • Ai Evaluations Engineer employment type Onsite
  • Ai Evaluations Engineer salary Full-time

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Job Title :

Ai Evaluations Engineer

Job Type :

Full-Time

Job Location :

New York New York United States

Remote :

No

Jobcon Logo Job Description :

Role: AI Evaluations Engineer (Senior)
Location: US (remote)
Duration: 12 Months +
Key Responsibilities
  • Design and operate end-to-end evaluation frameworks for agentic AI systems (offline regression, online monitoring, A/B testing)
  • Define quality rubrics, scoring architectures, and evaluation standards across multi-agent workflows
  • Build LLM-as-judge and Agent-as-judge pipelines assessing trajectory, tool-call accuracy, groundedness, and safety
  • Own and deliver evaluation infrastructure end-to-end; mentor teams and uplevel customers on evals best practices
Must Have
  • 5-7+ years building production-grade ML or GenAI systems; advanced Python
  • Hands-on experience with agent evaluation: offline/on-demand regression testing and online/continuous live-traffic scoring
  • LLM-as-judge proficiency: rubric design, scoring at session, response, and tool-call granularity
  • Core eval metrics: task completion, tool-call accuracy, trajectory quality, groundedness, safety
  • Agentic framework experience (Strands, LangGraph, CrewAI or similar)
  • AWS Bedrock (Models, Guardrails) + CloudWatch; Lambda, S3, IAM fundamentals
Should Have
  • Bedrock AgentCore Evaluations (on-demand SDK runner, online monitoring, A/B testing)
  • Agent-as-a-Judge framework; HITL evaluation pipelines
  • Benchmarking frameworks (tau-bench, SWE-bench, GAIA) and custom dataset construction
  • RAG quality evaluation (faithfulness, context precision, recall)
  • CI/CD integration for eval regression; observability tooling (tracing, structured logging)
  • Legacy technology familiarity (Java/Spring, Sybase, DB2, or COBOL) as source context for agentic modernization or integration pattern design
  • Financial services or regulated-industry experience (compliance-aware delivery: trade surveillance, data controls, audit requirements)
  • Large-scale portfolio delivery experience - reusable patterns or components applied across 50+ applications, including wave planning and throughput measurement

Jobcon Logo Position Details

Posted:

Oct 13, 2026

Reference Number:

4601-15867

Employment:

Full-time

City:

New York

Job Origin:

CIEPAL_ORGANIC_FEED

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Role: AI Evaluations Engineer (Senior)
Location: US (remote)
Duration: 12 Months +
Key Responsibilities
  • Design and operate end-to-end evaluation frameworks for agentic AI systems (offline regression, online monitoring, A/B testing)
  • Define quality rubrics, scoring architectures, and evaluation standards across multi-agent workflows
  • Build LLM-as-judge and Agent-as-judge pipelines assessing trajectory, tool-call accuracy, groundedness, and safety
  • Own and deliver evaluation infrastructure end-to-end; mentor teams and uplevel customers on evals best practices
Must Have
  • 5-7+ years building production-grade ML or GenAI systems; advanced Python
  • Hands-on experience with agent evaluation: offline/on-demand regression testing and online/continuous live-traffic scoring
  • LLM-as-judge proficiency: rubric design, scoring at session, response, and tool-call granularity
  • Core eval metrics: task completion, tool-call accuracy, trajectory quality, groundedness, safety
  • Agentic framework experience (Strands, LangGraph, CrewAI or similar)
  • AWS Bedrock (Models, Guardrails) + CloudWatch; Lambda, S3, IAM fundamentals
Should Have
  • Bedrock AgentCore Evaluations (on-demand SDK runner, online monitoring, A/B testing)
  • Agent-as-a-Judge framework; HITL evaluation pipelines
  • Benchmarking frameworks (tau-bench, SWE-bench, GAIA) and custom dataset construction
  • RAG quality evaluation (faithfulness, context precision, recall)
  • CI/CD integration for eval regression; observability tooling (tracing, structured logging)
  • Legacy technology familiarity (Java/Spring, Sybase, DB2, or COBOL) as source context for agentic modernization or integration pattern design
  • Financial services or regulated-industry experience (compliance-aware delivery: trade surveillance, data controls, audit requirements)
  • Large-scale portfolio delivery experience - reusable patterns or components applied across 50+ applications, including wave planning and throughput measurement

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