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Overview

JobLeap’s conversational search allows you to refine and explore job opportunities through natural follow-up questions. The AI remembers your conversation context, so you can iteratively narrow your search without repeating yourself.

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How It Works

1

Ask your initial question

Start with any job search query: “Data analyst jobs in Texas”
2

Review the AI's answer and job results

Browse through the summary and job cards provided
3

Ask follow-up questions

Refine based on what you see: “What about ones that don’t require SQL?”
4

Continue the conversation

The AI remembers context throughout your session: “Show me only the remote positions” “Which of these pay over $80k?”

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Conversation Examples

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Example 1: Narrowing by Requirements

You: "Data analyst jobs in Texas"

AI: Shows 50+ results with market summary

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Example 2: Exploring Alternatives

You: "Machine learning engineer positions in San Francisco"

AI: Shows 30 results with SF ML market insights

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Example 3: Company Research Flow

You: "Product manager jobs at AI startups"

AI: Shows 20 PM roles at various AI companies

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Types of Follow-up Questions

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Filtering Questions

Add or remove criteria from your search:
  • “What about ones that also require React?”
  • “Show me senior-level positions only”
  • “Which of these are at startups?”
  • “Filter for roles with equity compensation”
  • “What about ones that don’t require a Master’s degree?”
  • “Show me positions without on-call requirements”
  • “Which don’t need security clearance?”
  • “Filter out contract positions”
  • “What about mid-level instead of senior?”
  • “Show me hybrid instead of fully remote”
  • “Change location to Seattle”
  • “Look for Series B companies instead of Series A”
  • “Only show positions posted in the last week”
  • “Which of these offer visa sponsorship?”
  • “Show me companies with diversity initiatives”
  • “Filter for roles with relocation assistance”

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Exploratory Questions

Learn more about the results or market: 
"How do these salaries compare to other cities?"
"What's the difference between these two roles?"
"Which companies offer better benefits?"

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Clarification Questions

Get more details about specific results: 
"Tell me about the company culture at [Company]"
"What's [Company]'s remote work policy?"
"How is [Company] doing financially?"

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Conversation Best Practices

Take advantage of context memory:Good:
  • “Show me only remote positions” (after initial search)
  • “What about senior level?” (JobLeap knows what “what about” refers to)
  • “Which of these offer equity?” (refers to current result set)
Less Effective:
  • Starting completely new search mid-conversation
  • Ignoring previous results
  • Repeating full criteria each time
Reference previous results naturally:
  • “Which of these pay the most?”
  • “Tell me more about that company”
  • “Show me similar roles in other cities”
  • “What about ones without degree requirements?”
The AI understands context and will apply filters to the appropriate result set.
For best results, refine incrementally:Good:
  1. “Data scientist jobs in New York”
  2. “What about remote options?”
  3. “Show me only senior level”
  4. “Which pay over $150k?”
Less Effective:
  • “Remote senior data scientist jobs in New York paying over $150k” (all at once makes refinement harder)
Don’t be afraid to change direction:
  • “Actually, show me data engineer roles instead”
  • “Let’s try a different location—how about Austin?”
  • “Forget salary, which companies have the best culture?”
JobLeap understands pivots and will adjust the conversation flow.
Mix job searching with career research:
  • Search for jobs → Ask about salary trends → Return to search
  • Find roles → Research companies → Filter based on findings
  • Browse opportunities → Ask about required skills → Search for learning resources

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Advanced Conversation Techniques

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Comparison Queries

Compare different options directly: 
"Compare software engineer salaries in NYC vs. San Francisco"
"What's the difference between ML engineer and data scientist roles?"
"How does working at a startup compare to a big tech company?"

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Hypothetical Exploration

Explore “what if” scenarios: 
"What if I learned React—would that open more opportunities?"
"How much would my salary increase with a Master's degree?"
"What if I'm willing to relocate—where are the best opportunities?"

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Multi-step Refinement

Chain multiple filters in sequence:
1

Broad search

“Software engineer jobs”
2

Add location

“In the Pacific Northwest”
3

Specify level

“Senior positions”
4

Add tech stack

“Using Python and Go”
5

Company preference

“At companies under 200 employees”
6

Final filter

“That offer remote work”

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Context Retention

JobLeap remembers throughout your session:

Search Criteria

Previous filters, locations, and requirements

Job Preferences

Roles, companies, or skills you’ve shown interest in

Questions Asked

Topics you’ve explored and information you’ve sought

Result Sets

What jobs you’ve been viewing and discussing
Context resets when you close the browser or start a new session. For persistent preferences, consider creating an optional account.

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When to Start Fresh

Sometimes it’s better to begin a new search:
Start over if:
  • You want to search for a completely different role
  • Results have drifted too far from your original intent
  • You’ve applied many conflicting filters
  • The conversation feels confusing or stuck
How to reset:
  • Type a new, complete search query
  • Use “Let’s start over: [new search]”
  • Refresh the page for a clean slate

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Troubleshooting Conversations

If follow-ups aren’t working:
  • Rephrase with more explicit references
  • Try “In the previous results, show me…”
  • Start fresh with a complete query
If you’ve narrowed too much:
  • “Remove the salary filter”
  • “Broaden to include junior roles”
  • “Show me the original results again”
If you’re unsure where you are:
  • “Summarize what we’ve been searching for”
  • “Show me the current filters applied”
  • Start a new search with complete criteria

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Next Steps

Search Strategies

Advanced tips for effective job searching

Company Research

Deep dive into employers during your search

Salary Intelligence

Use conversation to explore compensation data

Start Searching

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