Interview scorecard template

Robotic Process Automation (RPA) Developer interview scorecard

Evaluate Robotic Process Automation (RPA) Developer candidates across 4 weighted areas: technical proficiency, systems and trade-offs, evidence and rigour, and collaboration and communication. Technical proficiency leads at 35%, so check hands-on depth in UiPath, Power Automate or Blue Prism: REFramework, selectors and dynamic UI, queue design, orchestrator triggers, plus C# or Python. Use the rubric to compare role-specific evidence consistently.

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TL;DR
For technical proficiency, look for evidence the candidate names specific frameworks and activities, explains selector repair, queue retry logic and custom library code they built rather than reused. For systems and trade-offs, look for evidence the candidate rejects unsuitable processes outright, argues for API-first where available, and sizes bot count against volume, SLA and licence spend. Apply the written 1–5 anchors to every answer, record the evidence behind each rating, and use the factor weights to reach a consistent overall assessment.
Complete evaluation framework

What to assess and how to score it

Review the evidence signals before interviewing. Then use the anchored descriptions—not instinct alone—to choose the score that best matches each answer.

01
Evaluation factor

Technical proficiency

35% weight

Check hands-on depth in UiPath, Power Automate or Blue Prism: REFramework, selectors and dynamic UI, queue design, orchestrator triggers, plus C# or Python custom activities.

Evidence to listen for

  • Command of the languages, frameworks, and data tools the role actually uses
  • Understands correctness, performance, and failure modes, not just syntax
  • Has opinions on testing and can justify them
  • Reads and reasons about code they did not write

Five-point scoring guide

1
Poor

Cannot work independently; fundamentals are missing.

2
Needs Improvement

Weak fundamentals; output needs heavy review.

3
Satisfactory

Competent for the role; needs guidance on complex or unfamiliar work.

4
Very Good

Strong practitioner; handles hard problems with little guidance.

5
Excellent

Names specific frameworks and activities, explains selector repair, queue retry logic and custom library code they built rather than reused.

02
Evaluation factor

Systems and trade-offs

25% weight

Probe how they choose attended versus unattended bots, when API or SQL integration beats UI automation, and how they handle credential vaults and licence cost.

Evidence to listen for

  • Reasons about scale, latency, cost, and failure before writing code
  • Names the trade-off they chose and what they gave up
  • Understands the data lifecycle end to end
  • Anticipates what breaks at ten times the volume

Five-point scoring guide

1
Poor

No thinking beyond the immediate task; no awareness of scale or failure.

2
Needs Improvement

Limited architectural awareness; struggles with design decisions.

3
Satisfactory

Works within an existing design; makes sound local decisions.

4
Very Good

Designs for scale and maintainability; articulates trade-offs clearly.

5
Excellent

Rejects unsuitable processes outright, argues for API-first where available, and sizes bot count against volume, SLA and licence spend.

03
Evaluation factor

Evidence and rigour

25% weight

Assess measured outcomes: hours saved, transaction success rate, exception ratios, and how they proved handling time before and after via process mining or log analysis.

Evidence to listen for

  • Validates results rather than trusting output
  • Knows how their work is measured and what a bad result looks like
  • Can describe a time their own analysis or model was wrong and how they caught it
  • Careful about data quality, leakage, and silent failure

Five-point scoring guide

1
Poor

Ships unvalidated work; no notion of how correctness is checked.

2
Needs Improvement

Validates superficially; misses obvious quality or leakage issues.

3
Satisfactory

Reasonable checks in place; rigour drops under time pressure.

4
Very Good

Validates thoroughly; can name a real error they caught in their own work.

5
Excellent

Quotes baseline versus post-automation metrics, cites exception rates from Orchestrator logs, and distinguishes claimed savings from audited ones.

04
Evaluation factor

Collaboration and communication

15% weight

Look for evidence of running process walkthroughs with business SMEs, producing PDDs and SDDs, and handling UAT sign-off plus hypercare after go-live.

Evidence to listen for

  • Explains technical work to non-technical stakeholders
  • Gives and takes code or peer review constructively
  • Documents enough that the work survives their absence
  • Aligns with team process rather than working around it

Five-point scoring guide

1
Poor

Cannot work in a team; resistant to feedback.

2
Needs Improvement

Communication issues create rework; lone-wolf tendencies.

3
Satisfactory

Adequate team member; documentation and review participation are light.

4
Very Good

Communicates well; reliable reviewer and collaborator.

5
Excellent

Describes PDD workshops with named business functions, negotiated scope changes, and support handover documentation that operations staff actually used.

Evidence-led prompts

Interview questions for a Robotic Process Automation (RPA) Developer

Use these prompts to surface evidence for the weighted factors above and compare candidates against the same role-specific criteria.

  1. 01

    Can you describe your experience with RPA tools such as UiPath, Blue Prism or Automation Anywhere?

  2. 02

    What is your experience with scripting languages such as Python or JavaScript in an RPA context?

  3. 03

    Have you integrated RPA solutions with systems such as ERP, CRM or databases?

  4. 04

    How do you approach process mapping and documentation before starting an RPA project?

  5. 05

    How do you assess the return on an RPA implementation?

See the complete Robotic Process Automation (RPA) Developer question set
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