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OverviewFeaturesComparePricingAPI

One API.

3,445 roles. 81 cities. 2030 projections.

See it work.Share your salary
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Data in
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Apple News+
Compensation

AI Engineer Salaries Hit Record Highs in Q2

Senior compensation packages now top half a million dollars in San Francisco, according to Orbyt Intelligence data covering 3,445 roles across 81 U.S. cities.

Sarah Lin · April 6, 2026 · 4 min read
Q3 ’25Q4 ’25Q1 ’26Q2 ’26
AI Engineer base salary, San Francisco. Orbyt Intelligence Estimate (modeled), not measured pay.

Orbyt's modeled base salary estimate for an AI Engineer in San Francisco now stands at $174,000, with total compensation reaching $246,000 including equity and bonus, according to Orbyt Intelligence. That is 1.3× the national baseline.

Bloomberg
Equity

Equity Now Half of Senior AI Pay Packages

Stock grants and signing bonuses have outpaced base salary growth at top-tier AI labs, according to Orbyt Intelligence annual data.

Marcus Chen · April 6, 2026 · 3 min read
2023202420252026
Equity as a share of senior AI compensation. Source: Orbyt Intelligence.

Equity grants and signing bonuses now account for 52% of total compensation packages at top AI labs, up from 38% two years ago, according to Orbyt Intelligence.

Reuters
Geography

San Francisco Pulls Away From Other AI Hubs

Bay Area senior AI engineers now out-earn their New York and Seattle peers by a wider margin than at any point in the last decade.

Priya Raman · April 6, 2026 · 3 min read
SFNYCSEAAUS
Senior AI Engineer total compensation by metro. Source: Orbyt Intelligence.

San Francisco senior AI engineers now earn 34% more than New York peers and 89% more than Austin, according to Orbyt Intelligence.

Claude Agent, querying the Intelligence MCP (Model Context Protocol) tool. Article preview is illustrative.

Apple, the Apple logo, and Apple News+ are trademarks of Apple Inc. Bloomberg is a trademark of Bloomberg L.P. Reuters is a trademark of Thomson Reuters. None of these companies are affiliated with or endorsing Orbyt. Article previews are illustrative.

Intelligent.

Ridiculously complete. Remarkably simple.

Six engines.

Role taxonomy, skill premiums, skill half-life, comp by stage, company signals, hiring velocity. Each engine has one job. Together they answer every comp question.

MCP server.

Six locked tools. Decision-Ready Responses. Stdio + HTTP transports. Drop into Claude Code, ChatGPT, or any MCP client.

lineage on every response.

Every data point carries a stable data_point_id. Resolve it to the full source trail: BLS, H-1B LCA, with weights and reconciliation rules. Per-point lineage is live for ingested data (Canada and UK today); US rows populate as the pipeline backfills.

Annual history + 2030 projections.

Quarterly snapshots of our computed estimate since Q2 2026. Year-by-year forecasts through 2030. Audit the methodology, and cite the published BLS wage that travels with every response.

Cite-ready responses.

Every call returns a methodology version, a citation field, a data_point_id, and confidence intervals. Quote it verbatim in papers, board decks, and compliance filings.

CLI + webhooks.

@orbyt/cli for terminal + CI/CD. Webhooks for data.refreshed, data.corrected, velocity.changed. Stripe-compatible signatures. Local-dev tunneling via the CLI.

Without the contract.

Built for teams who paid six figures
for last year’s numbers.

Cadence

Annual, not annual.

Survey-based incumbents refresh once a year. Your data is stale the day the PDF ships. Orbyt posts new snapshots every year.

Format

API, not PDF.

Incumbents deliver bound reports and Excel exports through a portal. Orbyt is a JSON API. Your platform consumes it directly.

Procurement

Self-serve, not sales-led.

No six-month sales cycle. No custom MSA. Start free, no card. Upgrade when you scale. Ship before procurement opens a ticket.

Rights

Cite-ready, not proprietary.

Every response ships with a citation field and published methodology. Quote it in papers, board decks, and compliance filings. Open license.

Common questions

Orbyt Intelligence. AI compensation, decoded. It ships as six engines for the AI labor market: AI Role Taxonomy (598 roles, BLS SOC mapped), AI Skill Premiums (dollar premium per skill), AI Skill Half-Life (decay curves on each premium), AI Comp by Funding Stage (seed through public), AI Company Signals (hiring intent + comp pressure + attrition), and AI Hiring Velocity (posting volume + time-to-fill + salary drift). All six surface through 20 REST endpoints and one MCP server with six locked tools. Lineage on every response. Built for AI research teams, HR tech platforms, and newsrooms.

Orbyt Intelligence is the only compensation platform built for AI roles first, and the only one with six purpose-built engines instead of a single salary lookup. 598 specialized job titles (Levels.fyi tracks roughly 100). Quantified skill premiums with confidence intervals and decay curves (no one else publishes these). Funding-stage compensation bands from seed to public per role. field-level provenance via /lineage on every data point. MCP server returning Decision-Ready Responses with citation.request_id traceability: drop into Claude Code, ChatGPT, or any MCP client.

AI Role Taxonomy resolves role identities (598 roles, eight families, eight seniority bands, BLS SOC codes, related-role graph). AI Skill Premiums quantifies the dollar premium each skill commands by role and city, with 95% CIs. AI Skill Half-Life models how fast each premium is decaying using exponential, logistic, or plateau curves. AI Comp by Funding Stage breaks comp down across seven stages from seed to public, with explicit equity-vs-cash math. AI Company Signals tracks per-company hiring intent, comp pressure, attrition risk, AI maturity, and pay transparency posture. AI Hiring Velocity measures posting volume, time-to-fill, salary drift, and competitive intensity per role × city.

The MCP server at /api/v1/intelligence/mcp is a JSON-RPC 2.0 endpoint exposing six locked tools: list_capabilities, analyze_compensation, analyze_skills, analyze_market, discover_roles_and_cities, find_adjacent_opportunities. Every tool returns a Decision-Ready Response with a quotable answer sentence, primary + supporting data, methodology citation, follow-up suggestions, and honest limitations. Stdio transport for Claude Code, HTTP transport for any agent. Same API key. Pro plan and above. See /orbyt-intelligence/mcp for the full integration guide.

Free is 1,000 requests a month at 60 requests per minute, with no card. AI Role Taxonomy engine (598 roles, 81 cities, BLS SOC mapping). The calculate and search endpoints. The published BLS wage benchmark that travels beside every estimate. CORS enabled. An API key IS required, because the monthly limit is counted per user and an anonymous request cannot be. Upgrade to Pro for the MCP server and the /lineage provenance endpoint.

Pro at $99/month adds 300 requests per minute, 250,000 requests a month, the MCP server, the /lineage provenance endpoint, restricted API keys with per-engine scopes, and priority support. 5 seats included. Most teams upgrade when they want to wire Orbyt into Claude Code via MCP, or when they need provenance on every figure they cite.

Ultra at $199/month includes 1,500 requests per minute, 500,000 requests a month, the company leveling catalog, the annual compensation reports, dedicated support, and custom data requests. 15 seats included.

Yes. Every response includes a citation field ready to quote verbatim, plus an assumptions array explaining methodology. The Dataset schema markup is verified and indexed by Google Dataset Search and Perplexity's answer engine. Suggested citation: "Orbyt Intelligence, May 2024. https://www.orbytlabs.ai/intelligence"

The salary figures are computed estimates, not observed wages: a national role baseline scaled by BEA Regional Price Parities. The published wage data Orbyt holds is BLS Occupational Employment and Wage Statistics, and Department of Labor H-1B Labor Condition Application filings (a filed minimum visa base wage, not market pay). Where BLS publishes a wage for the occupation a role maps to, it is shown alongside the estimate as a separate benchmark, labelled with its occupation code, metro area and worker count. Full methodology is published at /orbyt-intelligence/methodology.

Ship with it.

Two engines serving data. One MCP server. CLI for terminal + CI/CD.
Webhooks for events. OpenAPI spec. Full reference.

API docsAll six enginesMCPCLIWebhooksMethodologyInternational
Annual Compensation Report · 2026 · Free
The AI Compensation Report 2026.
85 pages of named-analyst research across three editions plus the full 3,445-role dataset. Every edition free this year. By Justin Bartak.
Read the report →Download full report

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