Ship faster without surprises on launch day.

I help CTOs, VPs and Directors of Engineering at fintech and regulated-data companies find out what will break before a launch. The first step is a fixed-fee Release Risk Diagnostic of about two to three weeks. I also advise on how teams are organized to deliver and on where AI can remove work, starting with testing. Previously Director of Enterprise Testing at Ford Credit.

Request a 30-minute conversation See the Release Risk Diagnostic

I work in English and Spanish with teams in the US and Mexico.

Built from zeroEnterprise Testing at Ford Credit and the B2B engineering organization at Jump
3 to 4 hoursTest data fulfillment at Ford Credit, down from 1 to 2 days
200,000 requests a secondNFL backend load test, twice the baseline
About $1M to $100K a yearNFL Fantasy Football hosting cost, after moving it off vendor-managed hardware

The Release Risk Diagnostic

Know your system's limits before launch day does. A fixed-fee engagement of about two to three weeks, scoped in a 30-minute call. It ends with a decision: stop with a plan in hand, or continue with an advisory retainer.

Request a 30-minute conversation

You receive five things:

A ranked list of release risks, each with the evidence behind it.
Load evidence for the critical path you choose: where it slows and where it breaks, stated as numbers.
A gap map of contract testing and quality gates across your services and pipelines.
A 90-day plan with owners and expected effect.
A one-page summary a board can read.

Where to start

A launch or platform cutover is coming and you are not sure it will hold.: Start with: Release Risk Diagnostic
Releases keep slipping, or customers report defects your tests missed.: Start with: Engineering Operating Model Review
A program needs outside assurance, or you want a senior sounding board for a few months.: Start with: Interim program assurance or an advisory retainer

About

I am Antonio Almazzo. I have led engineering organizations since 2022 and built two of them from zero: Enterprise Testing at Ford Credit and the B2B engineering organization at Jump (Mar 2022 to Jul 2023). I am an engineer first, with hands-on and leadership roles at the NFL, Ticketfly, Intercontinental Exchange (ICE), Shopzilla and Google, and I am a native Spanish speaker.

Sectors I have worked in: fintech and financial data (Ford Credit, Intercontinental Exchange), healthcare data (Episource), media (the NFL), and ticketing and entertainment (Ticketfly, Jump).

In 2024 I consulted part time for a fraud-prevention software company, building the reference GitHub Actions and Terraform pipeline that its new Java microservices follow on AWS. I hold an M.S. in Artificial Intelligence from Tecnológico de Monterrey.

I work alone, through Lucent Labs LLC, a California limited liability company. The person you talk to is the person who does the work.

Full background (PDF)

Work I can point to

Ford Credit

Director of Enterprise Testing, Jan 2025 to Oct 2026

The problem: A fintech modernization, with a 30-year-old estate running alongside new platforms, needed one testing model for teams in the US, Canada, Mexico, India and Europe.
What I did: I built the Enterprise Testing organization from the ground up and scaled it to three programs through enablement, not by owning each team's test suites. I consolidated four automation frameworks into one AI-assisted Playwright platform and led an in-house AI test-generation agent.
The result: Test data fulfillment fell from 1 to 2 days to 3 to 4 hours per account.
Test authoring time fell 66%, saving about 302 engineering hours in one quarter. Active users grew from 8 to 38 across 7 teams.
All 47 repositories moved to one standard, and 6 teams run 900+ tests on the new platform.
12 application teams passed performance validation with zero production impact.
Figures as of September 30, 2026.

Episource

Director of Engineering, Jul 2023 to Dec 2024

The problem: A healthcare data platform under HIPAA and GDPR needed realistic test data in lower environments, with no production PII or PHI reaching them.
What I did: I led enterprise quality engineering and implemented test data management. Data was masked with Delphix when it moved from production to lower environments, and validations and reports checked that no sensitive production data had leaked. I also set up CI/CD quality gates and Pact contract testing across the microservices, under a platform-plus-standards model.
The result: Compliance received the validation reports as evidence that production data was masked before it reached lower environments.
All product teams adopted the platform-plus-standards quality model.

Intercontinental Exchange (ICE)

Staff, then Principal Software Engineer, Aug 2017 to Mar 2022

The problem: When the new streaming pipeline went to production, company network bandwidth use rose to 80%, and an incident room was formed to find the cause.
What I did: I replaced the legacy .NET ingestion pipeline with a cloud-native one, then built the streaming pipeline for the data product. In lower environments I had already found that one Windows server was returning uncompressed payloads of about 1 MB. I brought that to the incident room and we turned on gzip. I also architected an event-driven platform for AI products with replay and backfill.
The result: Company network bandwidth use fell from 80% to 40%.

National Football League

Senior Manager, Software Engineering, Apr 2015 to Aug 2017

The problem: nfl.com and the mobile apps were moving from a legacy system to a new microservices backend, and the engineering team had not worked with microservices before.
What I did: I ran test engineering for NFL Media. I introduced consumer-driven contract testing with JSON schema validation in CI, and my team load-tested the new backend. We scaled up the MySQL transactional store to sustain the transaction load.
The result: The new backend was load-tested to 200,000 requests per second, twice the 100,000 baseline from a 2014 test of the old platform.
In year two I also led Fantasy Football engineering and moved it from vendor-managed hardware to the NFL data center, cutting hosting from about $1M to $100K a year.

Ticketfly

Performance Engineering Lead, then Manager, Software Engineering, Oct 2011 to Mar 2015

The problem: More than 100,000 people queued for Burning Man's 2014 ticket sale, far more than the platform could serve at once.
What I did: I made the platform white-label on Burning Man's own domain, worked out its limits, and put Queue-it in front so 7,000 buyers could purchase at a time while everyone else waited. Over my years there I also established the QA function, added New Relic monitoring and ran SLA validation in CI.
The result: The Associated Press reported that 38,000 tickets sold out in 44 minutes.

Where I help

Prove it holds: Find where a system slows and where it breaks before the day that matters, and state the limit as a number. Consumer-driven contract testing in CI, so teams change services without breaking their consumers. Replayable data pipelines that survive slow dependencies and bad payloads.Proof: the NFL backend, load-tested to 200,000 requests per second.
Organize the work: Testing and platform organizations, and operating models with roles, governance and KPIs, rolled out through enablement so the standards keep working after I leave. Bilingual leadership for teams split between the US and Latin America, including nearshore setups.Proof: Ford Credit, one testing model for teams in the US, Canada, Mexico, India and Europe.
Speed it up with AI: Release strategy, quality gates and test-data practice, plus agents that generate tests and analyze root causes, with written rules for what they may touch. I start with testing, where I have measured results, and I measure before and after.Proof: test authoring time down 66% and test data in 3 to 4 hours instead of 1 to 2 days, at Ford Credit.

Ways to work together

The Release Risk Diagnostic is a fixed fee, typically $12,000 to $24,000 depending on scope. Other fees are quoted in writing after the first conversation.

Release Risk Diagnostic: About 2 to 3 weeks. Fixed fee, typically $12,000 to $24,000.The five deliverables above and a readout session with your leadership.
Engineering Operating Model Review: About 2 to 3 weeks. Fixed fee.A current-state map of how work moves from plan to release, ranked constraints, a draft operating model with roles, governance and KPIs, and a 90-day plan.
Advisory retainer: 3 to 6 months, 3 to 5 days a month. Monthly fee.A weekly working session, monthly written priorities with a decision log, and review of designs and plans.
Interim program assurance: Capped scope. Day rate.A named assurance lead for one program: release gates, a risk register, weekly status and a handover document.

How an engagement runs

A 30-minute conversation. You tell me what you are launching or changing and what you are least sure will hold. If I am not the right person, I say so then.
NDA and scope. I sign yours or send a mutual one before I see anything. Scope, deliverables, dates and fee go into a written statement of work.
The work. You name a counterpart and give me read access to repositories, pipelines and dashboards, plus a few hours a week from two or three people. Load tests run in a production-like environment you provide, never in production.
Readout and handover. You get the deliverables in writing and a readout session, then decide whether to stop or continue.

In regulated environments I work with masked or synthetic data and do not need production PII or PHI. Outside the scope unless agreed separately: production changes, security testing, and personnel or HR advice.

Questions buyers ask

How is the fee set?: The Release Risk Diagnostic is a fixed fee, typically $12,000 to $24,000 depending on scope, written into the statement of work before I start. It is not billed by the hour. The retainer is a monthly fee and interim assurance is a day rate.
What do you need from us?: A named counterpart, read access to repositories, pipelines and dashboards, a production-like environment for load tests, and a few hours a week from two or three people.
Do you sign an NDA?: Yes. I sign yours or send a mutual one before I see anything.
Do you test in production or use real customer data?: No. Load tests run only in a production-like environment you provide, and I work with masked or synthetic data. I do not need production PII or PHI.
What happens after the Diagnostic?: You decide whether to stop with the plan in hand or continue with an advisory retainer.
Where do you work, and in which language?: Remotely from Redondo Beach, California, on Pacific time, and on site in the Los Angeles area by agreement. I work in English and Spanish with teams in the US and Mexico.
Who is it for?: A leader with a launch, platform cutover or major release in the next three to six months who needs evidence a board can read. If I am not the right person, I say so on the first call.
What is outside the scope?: Production changes, security testing, and personnel or HR advice, unless agreed separately.

Start with a conversation

Tell me what you are launching or changing, and what you are least sure will hold. I reply within one business day.

Prefer email? info@antonioalmazzo.com

Based in Redondo Beach, California (Pacific time). LinkedIn