Al Evaluation Engineer

Hybrid in Tampa, FL, US • Posted 1 day ago • Updated 1 day ago
Contract Corp To Corp
Contract W2
12 Months
Hybrid
Depends on Experience
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Fitment

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Job Details

Skills

  • Ragas
  • DeepEval
  • MLflow
  • LangSmith
  • Langfuss
  • Al evaluation

Summary

Al Evaluation Engineer

Tampa, FL

12+ months

LangSmith. Langfuss, Ragas, DeepEval, MLflow.

We are seeking an experienced Al Evaluation Engineer to define and implement evaluation strategies and success metrics for Al agents. In this role, you will be responsible for assessing task completion, correctness, groundedness, hallucination, tool usage, safety, consistency, and overall user experience of Al-driven systems. You will build comprehensive test scenarios, including edge and adversarial cases, and develop automated evaluation pipelines leveraging deterministic checks, LLM-as-a-Judge techniques, and custom evaluators. Your analysis will involve detailed examination of agent traces, prompts, retrievals, tool calls, and outputs to identify failure modes and performance bottlenecks. You will also conduct regression testing spanning changes in models, prompts, tools, and workflows. Establishing quality thresholds, monitoring dashboards, and release gates will be key to maintaining robust Al agent deployments. This role requires close collaboration with Al engineering, product, business, and risk teams to ensure continuous improvement in agent functionality and safety.

Responsibilities:

Define evaluation strategies and success metrics for Al agents.

Evaluate task completion, correctness, grounded Ness, hallucination, tool usage, safety, consistency, and user experience.

Build test scenarios, edge cases, and adversarial cases.

Develop automated eval pipelines using deterministic checks, LLM-as-a-Judge, and custom evaluators.

Analyze agent traces, prompts, retrieval, tool calls, and outputs to identify failure patterns.

Perform regression testing across model, prompt, tool, and workflow changes.

Establish quality thresholds, dashboards, and release gates.

Partner with Al engineering, product, business, and risk teams to continuously improve agent performance.

Skills:

Understanding of GenAI, LLMS, RAG, prompts, tool calling, and Al agents..

Python and experience working with APIs, JSON, datasets, and evaluation frameworks..

Ability to translate business expectations into measurable evaluation criteria.

Experience with Al evaluation / observability tools such as LangSmith, Langfuse, Ragas, DeepEval, MLflow, or similar is preferred..

Strong analytical, problem-solving, and experimentation mindset.

Education : At least a bachelor s degree (or equivalent experience) in Computer Science, Software Engineering, Electronics Engineering, Information Systems, or a closely related field is required for the project

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
  • Dice Id: 80181903
  • Position Id: 184IT_0916_05
  • Posted 1 day ago

Company Info

About iTech US, Inc.

iTechGRC enables businesses to collect and integrate risk, compliance, audit, and third-party vendor data across the organizational silos to derive actionable business intelligence. We are a part of iTechUS, Inc, which has been there for over 20 years and is a leading business growth solutions provider. The team has transformed over 500 companies in every industry, focusing on performance, reliability, security, flexibility, and cost-efficiency.

We established iTechGRC to provide and implement the next generation of integrated risk management solutions that utilize the latest technology to help you achieve risk and compliance objectives. Guided by the vision of our Chairman and Chief Executive Officer, Kishore Khandavalli, we go beyond standard checklist activities and instead employ a targeted and tailored approach for the unique GRC needs of each customer.

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