Forward Deployed Engineer

Lunon is an AI transformation consultancy headquartered in New York City. We work with companies that have real operating data and real customers but no one whose job it is to turn AI into working software for them. We don't hand over a deck and leave. We embed an engineer inside the business, ship into their environment, and stay until it runs without us. This role is that engineer.

You'll join a small team that has already taken one client from "we think AI could help" to a production system their team relies on every day. Your first engagement is with a portfolio company of a private equity firm whose product is call analytics: thousands of recorded conversations a day, and a business that wants to know what's in them and what to do about it. You'll work with the Lunon team and directly with the people on the client side whose jobs your software changes.

• This position is remote (US-based). Lunon is headquartered in New York City.

• Expect some travel to client sites, typically a few days at a time, fully covered.

What you will own

• A client engagement end to end. You sit with the people doing the work before you write code, find where AI and better software actually move their numbers, and decide what to build first.

• Production systems inside the client's environment: pipelines over speech, text, and event data, LLM-backed workflows with a human review step, and integrations with the CRMs, telephony, and data warehouses they already run.

• Reliability, observability, and security after launch. You deploy to the client's cloud, you own what happens at 2 a.m., and you make it boring.

• The scope. Business asks arrive as "can it just tell us why customers are calling." You turn that into shippable slices, and you say no to the ones that won't pay back.

• The handoff. You teach the client's team to operate what you built so it outlives the engagement, and you write it down well enough that the next engineer doesn't have to guess.

• Lunon's playbook. What you learn on one client becomes shared tooling, evals, and patterns for the next one.

What you will need to do the job

• You have 4+ years building and operating production software, including at least one system you owned from design through on-call.

• You have shipped something that uses LLMs or ML in a real workflow with real users, and you can talk about where it failed and what you did about it.

• You're comfortable across the stack: TypeScript or Python services, SQL and a relational database, a major cloud, CI/CD.

• You have worked directly with non-technical stakeholders and changed what you built because of what they told you.

• You can walk us through one project from the business problem to the thing in production, not just the architecture diagram.

• You can travel to client sites when needed and are authorized to work in the US.

What will make us love you

• You've built with speech-to-text, conversation analytics, or large volumes of unstructured text, and you have opinions about evals.

• You've done consulting, agency, or forward-deployed work and know how to be useful in someone else's building on day two.

• You've integrated with a CRM, a telephony platform, or a data warehouse, and you enjoy talking about what made it hard.

• You've worked with a private equity-backed company and understand what a value creation plan does to a roadmap.

• Ambiguity is interesting to you. The problem arrives as "we have all these calls" and you help turn it into a scoped, sequenced plan.

• You share work before it's finished and would rather be corrected early than praised late.

You might not be a good fit if

• You want a product roadmap handed to you. Here the roadmap comes from sitting next to the client's team for a week.

• You'd rather build the platform than the thing the client needs this month.

• You're uncomfortable being the only engineer in the room when a decision gets made.

Compensation

$180,000 to $200,000 base salary plus equity. Health, dental, and vision. Travel fully covered. Expect difficult problems, a small team that moves fast, and clients who notice when it works.

How we hire

• A 30-minute conversation with the team about what you've shipped and what we're building.

• A technical deep-dive on one system you owned, from the business problem to production.

• A working session on a real client problem with the team.

• References, then an offer. We aim to finish in two weeks.

Lunon is an equal opportunity employer. We welcome anyone who is hungry to learn, solve problems, and progress regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, or other legally protected characteristics. If you need an accommodation during the hiring process, let us know.

Beware of recruitment fraud. All official correspondence comes from a lunon.ai email address. We will never ask you to share bank account information, cash a check, or purchase equipment as part of the hiring process.