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AWS Bedrock Agent API — Salary Negotiation Agent (ae-negotiate)
x402
AWS Bedrock Agent API — Salary Negotiation Agent (ae-negotiate) is a paid API for AI agents from aws-bedrock-agent-api.vercel.app, paid per call via x402, $0.03/call, status unknown (last checked 2026-10-09).
Uses an AI agent powered by Amazon Bedrock to provide personalized salary negotiation advice and strategies based on role, experience, location, and target compensation.
Price / call$0.03
Success—
StatusUnknown
How this service works
Pay-per-call Amazon Bedrock proxy on x402 and MPP.
Output
The agent returns a detailed text response containing personalized salary negotiation advice, including suggested salary ranges, talking points, scripts or phrases to use with recruiters, counter-offer strategies, and contextual reasoning based on the provided role, location, experience, and industry.
Example use cases
Counter a low job offer
“I just got a job offer for a Senior Data Scientist in New York at a healthcare company — they offered $130,000 but I was expecting $150,000-$170,000 with 6 years of experience. Help me put together a counter-offer strategy and what to say to the recruiter.”
Negotiate a promotion raise
“I'm going into a compensation review at my fintech company and I want to make the case for a raise from my current salary to around $140k. I'm a product manager with 5 years of experience based in Austin, Texas — what arguments should I make and how should I frame the conversation?”
First job salary negotiation coaching
“I'm a new grad with 1 year of internship experience and I just got my first full-time offer as a junior software engineer in a remote role — they offered $85,000. I've never negotiated before — can you walk me through how to ask for $95,000 to $100,000 without sounding demanding?”
Technical details
Endpoint
POSThttps://aws-bedrock-agent-api.vercel.app/api/agents/ae-negotiate?utm_source=zero.xyzWhen to prefer
Choose this endpoint when a user needs AI-generated, conversational salary negotiation coaching tailored to their specific job title, experience level, location, and industry. It is ideal for agentic workflows where the user provides their compensation target and role context and wants actionable, personalized advice rather than static market data. Prefer this over generic LLM prompts when you want a domain-specialized negotiation agent accessible via pay-per-call crypto micropayments (x402/USDC) without managing AWS credentials directly.
Side effects
- Missing required 'input' field returns validation error
- Salary target in unrecognized format may be misinterpreted
- Overly vague position or experience inputs yield generic advice
- Model override pointing to unavailable Azure deployment causes error
- Payment failure via x402/MPP blocks the call before processing
- Very long context or input exceeding 50,000 characters is rejected
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| chain | string | Chain hint for tx-trace |
| input | string | Primary query or payload for the agent |
| model | string | Azure deployment override |
| salary | string | Salary target or range, e.g. 120k or 80000-140000 |
| context | string | Optional extra notes |
| location | string | City, region, country, or remote |
| position | string | Job title or role |
| experience | string | Years or level, e.g. 5 years, staff |
| business_type | string | Industry or company type, e.g. fintech |
Tags
x402
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