Senior Forward Deployed Engineer

About Praxent

Praxent builds software for financial services companies — banks, credit unions, lenders, insurers, and wealth platforms. We have been doing it for over twenty years, from Austin, with a delivery team spread across the US and Latin America.

We are an Anthropic partner, and building agentic AI systems inside our clients' environments is now a core part of the work rather than an experiment on the side. This role exists because that work needs a different kind of engineer than a traditional project team supplies — someone who sits with the client, decides what should get built, and builds it.

This is the first Forward Deployed Engineer hire at Praxent . You would be defining the role, not inheriting it.

This role has been categorized as a Remote position. “Remote” employees do not have a permanent corporate office workplace and, instead, work from a physical location of their choice which must be identified to the Company. Employees may live in the following locations: Texas, Colorado, Florida, Georgia, Massachusetts, Maryland, Minnesota, North Carolina, Nebraska, Oregon, Pennsylvania, Tennessee, South Carolina, Washington.

Applicants for this position must be currently and legally authorized to work in the United States without the need for current or future sponsorship (e.g., H-1B, J-1, F-1, CPT, OPT, etc.).

Praxent will not offer immigration sponsorship or assume sponsorship of an employment visa for this position.

International relocation or remote work arrangements outside of the U.S. will not be considered.
About the role

A Forward Deployed Engineer at Praxent embeds with a client, figures out what they actually need, and builds it. Not a spec handed down from a product manager — you are in the discovery conversation, you decide what gets built, and you ship it to production and stay until it works.

You will spend more than half your time in front of the people whose problem you are solving, and the rest of it writing the code that solves it. You are not shielded from the client. You are not handed a ticket queue. When a client asks for the wrong thing, talking them into the right thing is your job, not someone else's.

The shorthand we use internally is founder-level autonomy with staff-engineer-level rigor . You make the technical call in the room and defend it, rather than routing it back for sign-off. That is a real grant of authority, and it comes with real accountability for the outcome.

Financial services makes this harder and more interesting than it would be elsewhere. The systems are old, the data is regulated, the stakeholders are risk-averse for good reasons, and the gap between a working demo and something a bank will actually run in production is where most AI projects die. Closing that gap is the whole job.
What you'll do

- Own technical delivery end to end on your accounts — discovery, architecture, build, production, and the messy weeks after launch.

- Embed with client engineering and business teams. Translate a VP's business problem into an architecture, and that architecture back into language the VP can defend to their board.

- Build production applications and agentic systems inside client environments: LLM-backed workflows, agent orchestration, evaluation frameworks, and integrations against core banking, lending, policy administration, and financial data systems.

- Design the integration surface. Most of this work is API design and systems integration against platforms that were not built to be integrated with.

- Harden prototypes into systems a regulated institution will actually run — security review, audit trail, PII handling, performance under real load. The distance between a working demo and a production deployment at a bank is most of the job.

- Scope down. Identify when a client is asking for the wrong thing and talk them into the right thing. This is the part of the job we care most about.

- Guide the client's own engineers. Part of leaving well is tha