Staff Full-Stack Engineer

BetterUp•Austin, TX

1d•Hybrid

About The Position

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; Chicago, IL; 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. We're looking for a driven full stack software engineer who thrives at the intersection of data, automation, and product development. Someone who sees manual processes as opportunities for innovation, and who wants to build the intelligence infrastructure that transforms how organizations understand and develop their people. Performance Intelligence Our team is reframing BetterUp from a coaching vendor into a differentiated strategic partner through the "Performance Intelligence flywheel": talent insights → action at scale → proven ROI → more data → deeper insights → more impact. We're building the Intelligence Layer that unlocks BetterUp's vast unstructured data—session recordings, chat interactions, and behavioral signals—to deliver unprecedented workforce insights to our partners. We're at an inflection point. We've proven the concept with early partners, and now we need to scale. That means transforming manual, high-touch processes into automated, self-service capabilities that can serve hundreds of partners while maintaining the depth and quality of insights that make us unique. As part of the platform organization, you'll work in a data-driven environment building systems that democratize access to intelligence across our entire partner experience—from in-product Performance Intelligence features to consultative touchpoints with PICs, Partner Value teams, and Labs. You'll collaborate closely with Data Scientists and ML Engineers to operationalize cutting-edge models and make them accessible to the teams that drive partner value.

Requirements

7+ years relevant experience, at least part of which in a startup or high-growth environment
Strong software engineering practices (coding, unit testing, code reviews, design documentation and collaborative reviews)
Backend development: Experience with modern backend tech stacks (we use Ruby and Elixir, but expertise in Python, Node.js, Go, or similar is valued)
Frontend development: JavaScript/TypeScript, HTML5, CSS3 and knowledge of modern frontend frameworks
Experience building data pipelines, ETL processes, or working with large-scale data processing
Comfort working with both structured and unstructured data
Strong verbal and written communication skills
Alignment with BetterUp's mission of enabling self-driven behavior change

Nice To Haves

Experience with ML model operationalization or MLOps practices
Familiarity with data transformation and automation tools (Airflow, dbt, etc.)
Background in building internal tools and self-service platforms
Experience with Ruby, Elixir, Rails, EmberJS
Understanding of data warehousing, analytics platforms, or BI tools
Previous work on B2B SaaS products serving enterprise customers
Interest in organizational psychology, talent analytics, or HR tech

Responsibilities

Automation & Scale:
Architect and build automation tooling that reduces manual effort in insight generation and delivery by 75%, unlocking our ability to scale from 15-25 partners to hundreds
Design and implement data pipelines that systematically process unstructured data (session recordings, chat logs, behavioral signals) through our Intelligence Layer
Build self-service tooling that empowers cross-functional teams (PICs, Partner Value, Labs) to access and deliver insights without engineering bottlenecks
Develop monitoring and observability systems to ensure insight quality and pipeline reliability at scale
Product Engineering:
Collaborate with product, design, and data science to craft enterprise-grade experiences for Performance Intelligence features on our SPAs frontend (Ember, Lit) and backend services (Ruby, Elixir)
Build robust APIs and interfaces that surface Intelligence Layer capabilities across multiple touchpoints—both in-product and through consultative tools
Partner with ML Engineers and Data Scientists to operationalize unstructured data models and signal detection systems
Strong desire to delight enterprise customers and partners by building software that delivers actionable insights they can't get anywhere else
Infrastructure & Reliability:
Own your components during the entire lifecycle, from planning, development, deployment and maintenance phase
Build scalable and resilient systems using container technologies (Docker, K8s) and cloud infrastructure as code (AWS, Terraform)
Design data infrastructure that handles growing volumes of session recordings, chat data, and behavioral signals while maintaining performance and cost efficiency
Implement data quality checks and validation systems to ensure insight accuracy and reliability