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Austin, Texas, United States
Hybrid
Let's face it, a company whose mission is human transformation better have some fresh thinking about the employer/employee relationship.
We do. We can't cram it all in here, but you'll start noticing it from the first interview.
Even our candidate experience is different. And when you get an offer from us (and accept it), you get way more than a paycheck. You get a personal BetterUp Coach, a development plan, a trained and coached manager, the most amazing team you've ever met (yes, each with their own personal BetterUp Coach), and most importantly, work that matters.
This makes for a remarkably focused and fulfilling work experience. Frankly, it's not for everyone. But for people with fire in their belly, it's a game-changing, career-defining, soul-lifting move.
Join us and we promise you the most intense and fulfilling years of your career, doing life-changing work in a fun, inventive, soulful culture.
If that sounds exciting—and the job description below feels like a fit—we really should start talking.
We are a hybrid company with a focus on in-person collaboration when necessary. Employees are expected to be available to work from one of our office hubs at least two days per week, or eight days per month. Our US hub locations include: Austin, TX; New York City, NY; San Francisco, CA; and the Washington, DC metro area. If this is a role based in Europe, our Europe hub locations are London, UK and Amsterdam, NL. Please ensure you can realistically commit to this structure before applying.
AI is changing how every person in the world works. It's a new Industrial Revolution, and almost all of the attention is on the technology. Far less is going to the people who have to change how they work to use it.
We think helping people through that change is one of the most important problems in the world right now. Even the most technically advanced companies are struggling to get their workforces productive with AI, and our research shows much of the gap comes down to mindset and behavior, which can be coached. Coaching used to be something a company could afford only for its top leaders. With AI and human coaches working together, we can reach everyone, and the most iconic companies in the world are asking us to build that with them.
Our largest customers no longer decide on the demo. They decide on what happens after: whether their HR systems connect, whether provisioning works, whether coaching shows up inside the tools their people already have open, whether our AI behaves the way their risk team needs it to. Forward Deployment is the function that owns that work.
This role sets the technical architecture for Forward Deployment. Our largest customers are asking for the same few things in different words: the coach inside their own assistant, their data in their own lake, an AI deployment their governance committee will sign. Today we solve each of those one account at a time. You decide what the shared pattern is, build the first version on the hardest account, and make it what every squad uses and what the core platform eventually absorbs.
The accounts are specific. One customer wants our coach answering inside the agent platform it is rolling out to its whole workforce. Another is building its own experience layer on top of ours and needs an architecture where each experience is a declarative object instead of a custom build. A third signed, and then its AI governance committee asked how its data is hosted, whether it trains a model, and what happens under a legal hold.
You'll do this as a hands-on engineer, with squads of engineers and PMs around you, and you'll be the engineer we put in front of a customer's CTO, chief architect, or CISO when the technical answer decides the deal.
Set the architecture on the hardest accounts in the book. You walk into a customer whose environment we don't know yet and leave with a design their architects accept, our engineers can build, and core engineering can live with.
Decide whether we build, configure, or refuse. Some asks are a week of configuration, some are a real build, and some would fork the product. You make that call early, in writing, and you defend it to the customer and to our own leadership.
Own the pattern for putting the coach inside a customer's front door. That means agent-to-agent integration on standard protocols like MCP and A2A, into Copilot, Teams, and customers' own agent platforms, designed once so the fifth customer is configuration.
Write the engineering standards for Forward Deployment. The security bar for customer-facing builds, sandbox and data isolation, customer-data handling, and what "ready to graduate" means. Our code touches HR systems and member data at customers who run us through security review, and the standards are yours to write and hold.
Own the seam with core engineering. Every custom build ends one of three ways: it graduates into the platform with core engineering's acceptance, it converts to paid work, or we kill it. You make the technical case at the monthly graduation board, and you design builds so the ones worth keeping can be accepted cleanly.
Build the shared deployment infrastructure. A real customer sandbox, the tooling that turns a customer's own material into a working context library, and the evaluation harness that tells us whether a configured coach behaves the way that customer needs. Each new account should start from what the last one built.
Carry the technical relationship where the decision sits. You'll work with a customer's CTO, CISO, and enterprise architects, and you'll write the answers on data hosting, model training, and legal holds that their governance committee asks for.
Keep building. You write code on the hardest problems yourself, and the first version of every shared pattern is yours.
Raise the bar for every Forward Deployed engineer. You won't manage people. The way you design, review, and document becomes how the other squads work.
10+ years building and shipping production software, including several years as the technical owner of systems deployed inside large enterprises.
A record of leading the technical side of customer deployments where the contract value ran into seven or eight figures.
Architecture depth across identity, data, and integration: single sign-on and provisioning, HRIS, data pipelines, and multi-tenant isolation. You've designed for a customer's security review and passed it.
Production experience with LLM and agent systems: tool use, retrieval and context, guardrails, and evaluation. You've been accountable for how an AI system behaved in front of real users.
Credibility with senior technical audiences on both sides of the table. You've briefed a customer's CTO or CISO and your own engineering leadership, and you've delivered bad news to both without losing the room.
A record of turning one-off customer work into platform capability, and of killing the work that didn't deserve it.
Experience with agent protocols (MCP, A2A) or building inside Microsoft Teams, Copilot, or Slack is a plus.
Domain expertise in organizational transformation, human transformation, or talent intelligence is a plus.
Relentless agency. When something isn't working, you own it and fix it instead of naming the team that should have. Humility about what you don't know, and relentlessness about figuring it out anyway.
Architectural judgment under ambiguity. You pick the simplest design that survives the customer's constraints, and you can say what would make you change it.
The discipline to say no. A happy customer asking for one more thing is the hardest no in this job, and so is telling your own leadership that an ask would fork the product. You can do both without damaging the relationship.
Judgment about what generalizes. You can tell a custom build worth paving into the platform from one customer's snowflake, and you'll argue for the distinction in front of core engineering.
Executive technical communication. You can write the architecture note a CISO's team will read, and explain the same decision to a Chief People Officer in two minutes.
AI-native fluency. Building with agents is your default operating method, and you set the practices the rest of the team builds with.
Comfort deciding on incomplete information. You listen, synthesize, decide, and move. When you're wrong you correct fast and say so. You don't stall waiting for consensus.
Senior forward deployed engineers and deployment leads from companies that run this model, who have owned the architecture across several accounts.
Staff and principal engineers or architects from enterprise platforms in identity, HR technology, or data, who know how large customers' systems behave once they're deployed.
Founders, CTOs, and founding engineers who sold into large enterprises and carried the security review themselves.
Applied AI leads who have put agent or LLM systems into production at large companies and answered for how they behaved.
Helping people adapt while AI changes how work gets done is one of the most important problems in the world right now. You'll work on it across entire workforces at many of the world's largest employers, a bigger scale than any one company's internal team gets.
You set the architecture for a function our executive team has named as its expansion lever, on the accounts where the technical answer decides the outcome.
Your work sits on the critical path of decisions worth millions of dollars, and you'll know within a quarter whether it moved them.
You'll build for some of the largest companies in the world, in their environment, with their engineers and architects. Nobody stands between you and the customer. If that's not appealing, this isn't the right role.
The custom work has somewhere to go. A monthly graduation board with core engineering decides what becomes a platform capability, and you're the one making the technical case.
The problems are current. Agent-to-agent integration, enterprise AI governance, and evaluating how a coach behaves across tens of thousands of people are open problems, and you'll work on them with customers who need answers this quarter.
Forward Deployment is a young function with unwritten rules. The person in this seat writes the technical ones.
AI at BetterUp
Our team thrives at the intersection of human expertise and AI capability. As an AI-forward company, adaptation and continuous learning are part of our daily work. We're looking for teammates who are excited to evolve alongside technology – people who experiment boldly, share their discoveries openly, and help define best practices for AI-augmented work. These professionals thoughtfully integrate AI into their work to deliver exceptional results while maintaining the human judgment and creativity that drives real innovation.
Benefits:
At BetterUp, we are committed to living out our mission every day and that starts with providing benefits that allow our employees to care for themselves, support their families, and give back to their community.
Access to BetterUp coaching; one for you and one for a friend or family member
A competitive compensation plan with opportunity for advancement
Medical, dental, and vision insurance
Flexible paid time off
Per year:
All federal/statutory holidays observed
4 BetterUp Inner Workdays (https://www.betterup.co/inner-work)
5 Volunteer Days to give back
Company wide Summer & Winter breaks
Year-round charitable contribution of your choice on behalf of BetterUp
401(k) self contribution
We are dedicated to building diverse teams that fuel an authentic workplace and sense of belonging for each and every employee. We know applying for a job can be intimidating, please don’t hesitate to reach out — we encourage everyone interested in joining us to apply.
BetterUp Inc. provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, disability, genetics, gender, sexual orientation, age, marital status, veteran status. In addition to federal law requirements, BetterUp Inc. complies with applicable state and local laws governing nondiscrimination in employment in every location in which the company has facilities. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.
At BetterUp, we compensate our employees fairly for their work. Base salary is determined by job-related experience, education/training, residence location, as well as market indicators. The range below is representative of base salary only and does not include equity, sales bonus plans (when applicable) and benefits. This range may be modified in the future.
The base salary range for this role is as follows:
New York City and San Francisco: $250,000 - $320,000
Austin and Arlington: $230,000 - $285,000
Protecting your privacy and treating your personal information with care is very important to us, and central to the entire BetterUp family. By submitting your application, you acknowledge that your personal information will be processed in accordance with our Applicant Privacy Notice. If you have any questions about the privacy of your personal information or your rights with regards to your personal information, please reach out to support@betterup.co
