Agent Evaluation & Instrumentation Engineer

Job Description - AI Evaluation & Instrumentation Engineer

SECTION A: POSITION SUMMARY

State the objective and purpose of the role.

Serve as the technical evaluator within the team, responsible for the design, calibration, and adjudication of evaluation suites and gate thresholds across agent archetypes. Lead gate reviews under the Team Lead s authority, own the regression-pack methodology for AI/ML model changes, and act as the technical custodian of evaluation quality and drift hygiene.

SECTION B: KEY RESPONSIBILITIES AND RESULTS

Indicate key responsibilities and performance indicators of this role.

For existing role, please indicate additional responsibilities in bold.

1. Design and maintain offline evaluation suites (golden sets, regression packs, adversarial/safety probes) and the continuous-evaluation scoring pipeline across archetypes. 2. Conduct operability gate reviews: assess evidence packs, reproduce evaluation results, and recommend go/no-go with documented findings. 3. Own the model-update regression pack methodology and adjudicate regression runs against archived baselines with AIML Operations team. 4. Calibrate gate thresholds against production reality and maintain evaluation drift hygiene (golden-set rotation, hold-out sets, judge calibration). 5. Produce the monthly quality report per agent: eval trends, failure-mode taxonomy, and defect clusters with reproduction traces. 6. Mentor members of the team when needed and review their work for quality and consistency.

SECTION C: QUALIFICATIONS / EXPERIENCE / KNOWLEDGE REQUIRED

Indicate key knowledge and skills required for this role to perform the tasks to a satisfactory level. To also specify a suitable level of qualification required (i.e. basic, advanced, or professional), where applicable.

Category Essential for this role Good to have Education and Qualifications Bachelor s or Master s degree in Computer Science or a related field Work Experience

6+ years in ML/data/software with strong evaluation or quality focus

• Hands-on experience evaluating LLM or ML systems

Experience with agentic systems or RAG pipelines

Telco AI domain

Technical / Professional Skills

Please provide at least 3

LLM/agent evaluation design and statistical rigour

Python and evaluation tooling (promptfoo, DeepEval, or custom harnesses)

Data analysis and metric interpretation

Tracing/observability tooling

Adversarial testing / red-teaming Non-Technical / Soft Skills

Analytical rigour and attention to detail

Clear technical writing for gate findings

Ability to influence build teams on quality

• Management presentation Other Task-Specific Knowledge Understanding of telco customer intents and journeys - Responsible-AI and safety evaluation practices

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