# Deployment Strategist

**Company:** [Valon](https://hotfix.jobs/companies/valon)
**Location:** New York, NY, San Francisco, CA
**Role:** Solutions Architecture
**Salary:** $140k – $240k/yr
**Skills:** SQL, Python, Data Analysis, Workflow Configuration, Stakeholder Management, Process Mapping, AI Tools, Data Investigation, Executive Communication, Problem Solving
**Posted:** 2026-06-04

> Own live enterprise deployments of ValonOS into regulated mortgage servicing operations. Diagnose client workflows, configure solutions, drive decisions with data and code, and stay accountable until measurable business outcomes are achieved.

## Job Description

## What you will do
- Map a client's current operation, identify the gaps to ValonOS, sequence the roadmap, and get sign-off from leaders who have been doing this for 25 years.
- Query 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 drive a decision the business is willing to bet on.
- Translate between groups that do not naturally talk to each other: engineering, the client's servicing operations team, capital partners, compliance, product, and executives.
- Sit onsite watching foreclosure, escrow, loss mitigation, or cash operations specialists work, then come back and help rebuild the workflow.
- Configure and deploy the solution, watch client operators actually use it, and stay accountable for whether the workflow produces the measurable business outcome.
- Brief everyone else. The work starts with raw data, raw code, and raw conversations, and ends in a decision the business commits to.

## How we work
- Own the outcome, not the recommendation. Configure, deploy, iterate, and measure the result. Contracts are performance-based.
- Figure it out under incomplete data, undocumented legacy behavior, tense client tradeoffs, and unclear ownership.
- Build alignment, but do not hide behind consensus. 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. Use coding agents, build custom skills, and develop an internal knowledge layer (DeploymentOS).
- Write the playbook, not execute one. Every framework was built by someone in this seat figuring it out for the first time.

## What success looks like
- 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.
- Move fast without becoming sloppy. Energized by incomplete context.
- Reason through a regulated operating system from first principles.
- Use SQL, Python, AI tools, conversations, documents, and judgment to answer the question yourself.
- Hold a room of senior client leaders and still go low-level enough to debug a workflow, query, data pipeline, or operating edge case.
- Turn ambiguity into a plan, a decision, and a measurable result.
- If managing people, sharpen the pod: clearer decisions, faster learning loops, better client trust, and stronger ICs.

## Who thrives here
- People who have repeatedly been handed messy, important problems and found a way through.
- High-horsepower operators, consultants, bankers, investors.

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**Apply:** https://hotfix.jobs/jobs/b4ab7ff6-cd60-4ea8-9a8b-1b8a90787d98
**Canonical:** https://hotfix.jobs/jobs/b4ab7ff6-cd60-4ea8-9a8b-1b8a90787d98