Deployment Strategist
Valon
Deployment Strategist
Valon is building the AI-native operating system for regulated finance, starting with mortgage servicing. We're a Series C company backed by a16z, transforming industries that others have written off as too complex to innovate. Rather than build on top of broken legacy systems, we took a different approach: we built and operate our own mortgage servicing business managing $110+ billion in loans. This wasn't the end goal, it was how we deeply understood the complexity needed to build software that actually works in regulated industries. The results speak for themselves. We've transformed mortgage servicing from a 0% margin business into 60%+ margins while dramatically improving customer experience. Major enterprise contracts are now deploying across the industry. ValonOS is our unified platform that makes every process structured and programmable and it is perfectly positioned for the AI era. When everything flows through one system with rich data, AI agents don't just automate tasks, they continuously improve entire operations. Mortgage servicing is just the beginning of our vision to transform regulated industries and beyond.
Deployment Strategists own live enterprise deployments of ValonOS: part operator, part product strategist, part data investigator, and part executive translator. You diagnose how a regulated servicing operation works, decide what needs to change, configure the solution, and stay accountable until client operators are live and the business outcome is measurable.
The job is not to make recommendations from the outside. The job is to figure out what is true, make the right call under ambiguity, and drive the work until the outcome exists in the real world.
How many times in your career are you going to get the chance to deploy an eight- or nine-figure software contract into one of the most regulated industries on the planet?
Not many. That's what we do here.
Valon is the AI-native operating system for mortgage servicing - a $13 trillion industry running on infrastructure built before the iPhone. We did not try to fix it from the outside. We bought our way in: built and operate our own mortgage servicing business managing $110B+ in loans, used that operation to deeply understand every workflow that breaks at scale, and then built the software we wished existed.
The result: a 0% margin business turned 60%+. Our own servicing operation runs at 4x the employee efficiency of the industry. Major enterprise servicers - including Newrez - are now deploying ValonOS across the industry. The contracts we are rolling out are some of the largest and most complex enterprise software deployments anywhere in financial services right now.
Deployment Strategists are the people who make those rollouts actually work.
Every monthly payment from a homeowner triggers a chain reaction: money has to move, accounting entries have to balance, escrow has to disburse to the right counties and insurers, and every step has to satisfy regulators across all 50 states - each with its own foreclosure rules, notice timelines, fee restrictions, and licensing regimes. Get any of it wrong and you have created a CFPB headline.
Now do that for millions of loans, with hundreds of legacy vendors, dozens of capital partners, and operators who have been doing it one way for 30 years.
Mortgage servicing has resisted software automation for decades not because the individual problems are unsolvable, but because the abstractions are so hard to model correctly that no one had done it. We did. It took six years. Now we are deploying it across the industry - and that is where you come in.
A client recently described what we do as "open-heart surgery while the patient is still walking around running their business." That is accurate. You are handed a multi-decade-old operation processing hundreds of thousands of loans, with a reputation, a regulator, and a P&L - and you have to migrate it onto our platform without anything breaking. Under tight timelines. With executives watching.
A Deployment Strategist:
Maps a client's current operation, identifies the gaps to ValonOS, sequences the roadmap, and gets sign-off from leaders who have been doing this for 25 years.
Spends Tuesday querying the data warehouse to figure out whether a payoff event has actually occurred across our system, the servicer's ops, and a capital partner's books - and then drives a decision the business is willing to bet on.
Translates between groups that do not naturally talk to each other: engineering, the client's servicing operations team, capital partners, compliance, product, and executives.
Sits onsite watching foreclosure, escrow, loss mitigation, or cash operations specialists work, then comes back and helps rebuild the workflow.
Configures and deploys the solution, watches client operators actually use it, and stays accountable for whether the workflow produces the measurable business outcome.
Briefs everyone else. The DS does not get briefed. The work starts with raw data, raw code, and raw conversations, and ends in a decision the business commits to.
A few things we actually believe, not aspirationally:
You own the outcome, not the recommendation. This is the anti-consulting role. You do not hand off a deck and walk away. You configure, deploy, iterate, and measure the result. Our contracts are performance-based, so when your deployment works, Valon wins. Your work shows up in the P&L.
You figure it out. There will be incomplete data, undocumented legacy behavior, tense client tradeoffs, and unclear ownership. The job is to create clarity anyway.
You build alignment, but you do not hide behind consensus. You synthesize, recommend, commit, and defend the decision with evidence.
Code and data beat decks. A working query, a real workflow, a shipped change, or a clear operating decision wins over prettier slides.
AI fluency is how the work gets done, not a nice-to-have. Our team uses coding agents, builds custom skills, and develops an internal knowledge layer, DeploymentOS, that you will use and extend. Our highest performers do not just use these tools - they tell our engineers what to build next and ship workflows themselves when waiting would be too slow.
You are writing the playbook, not executing one. Every framework we use was built by someone in this seat figuring it out for the first time. The next versions will be written by you.
You are succeeding here if senior leaders trust you with ambiguous, high-stakes problems and feel the work is in safe hands.
That means:
You can walk into a domain you do not understand, build a working model quickly, find the data and people who matter, make a recommendation, and drive it to an operational outcome.
You move fast without becoming sloppy. You are energized by incomplete context, not paralyzed by it.
You can reason through a regulated operating system from first principles instead of relying on generic frameworks or waiting for a subject-matter expert to hand you the answer.
You use SQL, Python, AI tools, conversations, documents, and judgment to answer the question yourself.
You can hold a room of senior client leaders and still go low-level enough to debug a workflow, query, data pipeline, or operating edge case.
You turn ambiguity into a plan, a decision, and a measurable result.
If you manage people, your pod gets sharper because of you: clearer decisions, faster learning loops, better client trust, and stronger ICs.
The strongest people in this role have raw problem-solving horsepower plus ownership maturity. They are high-velocity operators who can grow into safe-hands operating leaders.
This role is for people who have repeatedly been handed messy, important problems and found a way through.
We are especially excited by high-horsepower operators, consultants, bankers, investors, Chiefs of Staff, founders, product or business operators, and people from other intense environments who have had to solve ambiguous problems under pressure. The common thread is not pedigree. It is speed of learning, quality of judgment, and willingness to own the outcome.
You may be a fit if:
You are restless around ambiguity. You do not need perfect context to start making progress.
You have taught yourself new tools because the work demanded it.
$215k - $250k
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