> ## Documentation Index
> Fetch the complete documentation index at: https://docs.techeval.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Seniority Levels: Tailoring Interviews by Experience

> Kovi adapts question depth and scoring for three seniority tiers—Junior, Mid-Level, and Senior—so every candidate receives a fair, calibrated evaluation.

Kovi uses seniority levels to calibrate question difficulty, expected answer depth, and scoring rubrics for every interview session. Rather than applying a one-size-fits-all evaluation, Kovi adapts its line of questioning based on the years of experience and role scope you define — so a junior engineer is never penalized for not knowing distributed consensus protocols, and a senior architect is never let off the hook with a surface-level answer.

## Seniority Tiers at a Glance

| Level | `evaluation_level` API Value | Focus Areas |
| - | - | - |
| **Junior / Foundation** | `"Junior"` | Core language fundamentals, basic data structures, simple algorithms, and foundational problem-solving patterns |
| **Mid / Execution** | `"Mid-Level to Senior"` | Production patterns, system integration, code optimization, debugging under constraints, and API design |
| **Senior / Architecture** | `"Senior to Architect"` | Distributed systems design, team leadership, architectural trade-offs, cross-team technical decision-making |

## Setting Evaluation Level in the SDK

Pass the `evaluation_level` parameter in your `schedule_interview()` call to tell Kovi which tier to apply. The value must exactly match one of the strings in the table above.

```python theme={null}
from kovi import KoviClient

client = KoviClient(api_key="YOUR_LIVE_API_KEY_HERE")

response = client.schedule_interview(
    job_id="JD-BE-4401",
    candidate_name="Alex Johnson",
    candidate_email="alex.j@example.com",
    mobile_number="+1-5550005678",
    role="AI Engineer",
    interview_type="Technical Deep Dive",
    evaluation_level="Mid-Level to Senior",   # Seniority tier
    tech_stack=["Python", "LangChain", "FastAPI", "Pinecone"],
    duration=30,
    pass_score=6.5,
    deadline_hours=72
)

print(f"Interview link: {response.get('interviewUrl')}")
```

## How Scoring Adapts

Kovi uses the same 0–10 scoring scale and the same `pass_score` threshold across all seniority tiers, but the underlying rubric shifts to reflect level-appropriate expectations. When Kovi grades a response, it benchmarks the answer against what a strong candidate at *that specific level* should demonstrate — not against a universal absolute standard.

In practice, this means:

* A **Junior** candidate scoring `6.5` has demonstrated solid command of fundamentals and clear communication for their experience level.
* A **Mid-Level to Senior** candidate scoring `6.5` has shown they can reason through production problems, optimize code, and integrate systems effectively.
* A **Senior to Architect** candidate scoring `6.5` has articulated credible architectural trade-offs, distributed systems thinking, and leadership judgment.

The same numeric score therefore represents meaningfully different demonstrated capability depending on the tier. You can apply a consistent pass threshold across all your roles without inadvertently penalizing less-experienced candidates or lowering the bar for senior hires.

<Note>
  We recommend setting your `pass_score` between **6.3 and 7.5** for all seniority levels. As a calibration reference, a highly capable candidate benchmarked at approximately 130 IQ typically scores around **6.5** — use this as your baseline when deciding where to set the threshold for a given role.
</Note>


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