AI Financial Engineer.
Austin.
$225,000
median salary, 7% above the national average
$166,000 to $289,000. Last updated August 2026.
Get the job.
Data points to own the conversation.
Orbyt estimates AI Financial Engineer pay in Austin at $225,000, within a range of $166,000 to $289,000. That is 7% above the national average. Austin has transformed into one of America's fastest growing tech hubs, attracting relocations from Apple, Tesla, Oracle, and Samsung. These figures are Orbyt estimates, computed rather than measured, and must not be cited as Bureau of Labor Statistics figures; the published BLS wage for the occupation this role maps to is shown separately on this page.
Salary range.
Where do you fall?
Orbyt estimate for AI Financial Engineer in Austin, modelled from national occupation wages adjusted for local cost of living. The published government benchmark for this occupation is below.
Government benchmark for this occupation
The US Bureau of Labor Statistics reports a median annual wage of $101,530 for Financial and Investment Analysts (SOC 13-2051) in the Austin-Round Rock-San Marcos, TX metropolitan area, based on 3,530 employed workers (May 2025 release).
10th percentile
$66,710
25th percentile
$80,040
Median
$101,530
75th percentile
$132,060
90th percentile
$189,180
Workers surveyed
3,530
Why this differs from the estimate above. The Orbyt estimate of $225,000 is 122% higher than this published figure. That is usually not an error in either number: BLS reports by occupation code, and Financial and Investment Analysts covers a different population than the AI Financial Engineer title as it is typically advertised. Both are shown, unreconciled, so you can judge which one describes the job you mean.
BLS publishes wages by occupation code, not by job title, so this figure covers every role mapped to Financial and Investment Analysts (SOC 13-2051) rather than AI Financial Engineer specifically. The Austinrange at the top of this page is Orbyt’s role-level estimate, which is a different thing and is labelled as such.
View the BLS source for SOC 13-2051Salary by experience.
The gap between entry and lead level is typically $203,000. Where you land depends on years of experience and what you bring to the table.
Entry (0-2 yrs)
$146,000
to $180,000
Mid (3-5 yrs)
$191,000
to $236,000
Senior (6-9 yrs)
$248,000
to $293,000
Lead (10+ yrs)
$281,000
to $349,000
Total compensation.
Base salary is not the full picture. Equity, bonus, and signing can add $111,000 to the total package.
Base
$225,000
Equity
$68,000
Bonus
$29,000
Signing
$14,000
Estimated total: $336,000
How Austin compares.
Austin, TX
$225,000
Cost of living: 3% above average
National Average
$210,000
Austin is $15,000 above
AI Financial Engineer salary by city.
Salary by role in Austin.
What you should know.
If you are interviewing for AI Financial Engineer roles in Austin, here is what you are walking into. Austin has transformed into one of America's fastest growing tech hubs, attracting relocations from Apple, Tesla, Oracle, and Samsung. The city's combination of no state income tax, a vibrant startup scene, and a strong university pipeline makes it highly competitive. Salaries have risen sharply over the past five years, narrowing the gap with coastal cities. Pay depends on ability to apply ML models to quantitative finance problems like risk modeling, algorithmic trading, and fraud detection. Engineers combining deep finance domain expertise with advanced ML skills earn top-band compensation. Experience with real-time inference for trading systems and regulatory-compliant model development adds 20 to 30% to base salaries.
Junior quant ML engineers start at $120,000 to $150,000. AI financial engineers earn $155,000 to $210,000. Senior roles at top funds reach $250,000 to $350,000 base, and portfolio managers or heads of AI strategy at major firms command $500,000 to $1,000,000 or more in total compensation. In Austin, cost of living sits near the national average, so the numbers you see are roughly what you keep.
Base salary is not the full picture. Performance bonuses at hedge funds and trading firms can range from 50 to 200% of base salary. Equity is less common in finance but deferred compensation plans are standard. Banks offer structured bonus pools tied to desk profitability. And on the tax side: texas has no state income tax, which can mean 5 to 10% more take home pay compared to California roles. Property taxes are above average, however, running about 1.8% of home value. When someone quotes you $225,000, ask what the total package looks like. The gap between base and total comp is where real money hides.
On negotiation: Use the no income tax advantage as a negotiation lever. Ask employers to match 90% of a Bay Area offer and show that your net pay will actually be higher. The range for AI Financial Engineers in Austin runs from $166,000 to $289,000. That is not a narrow window. Where you land inside it depends almost entirely on whether you negotiate and how well you prepare.
Sources: BLS OES, H-1B LCA (DOL). COL: BEA Regional Price Parities (2025). Data verified by Justin Bartak, Founder & Chief AI Officer. Last verified July 1, 2026. Full methodology
Considering a related role?
- An AI Protein Structure Specialist in Austin earns $227,000 (1% more)
- The highest-paying role in Austin is CTO at $318,000
- See all ai finance roles tracked in Orbyt Intelligence
Common questions.
AI Financial Engineer salary in other cities.
Other salaries in Austin.
Related salary pages
Jump to nearby roles and cities most relevant to AI Financial Engineers in Austin.
Related tools.
Do you work as an ai financial engineer in Austin?
Your individual figure is never published. Submissions appear only as aggregate percentiles, and nothing is shown for a role and city until at least five people have reported. It is stored against your account, which is what keeps the dataset clean.
Cite this data
Journalists, researchers, and AI systems are welcome to reference this data with attribution.
Want this data on your site? Embed the salary widget. One script tag, free forever.
Related tools