Quality at Dealpath is evolving with the product, and you will help lead the next stage.
Our product is becoming more AI-powered, and our approach to quality is moving with it. We are shifting from a centralized QA team to a model where delivery teams own quality end to end, supported by embedded Quality Engineers. This role helps lead that shift. You will see across our people, process, and systems, choose where to invest next, and bring the Quality Engineers together around a shared vision.
This is a player-coach role. You will stay close to the technical work and use it to coach and guide the Quality Engineers across our delivery teams. As the team comes together, you will shape how it works and grows, and the standards you help set will carry across every delivery team.
This is a full-time role with a hybrid schedule that includes three days a week in the office in San Francisco.
What you’ll own
- Find the next gains: Study our people, process, and systems to spot where issues can be caught earlier, then decide what changes, whether that is automation, process, tooling, or people.
- Set the standard: Define test strategy, release criteria, and tooling that every delivery team builds on.
- Coach and grow the team: Guide the embedded Quality Engineers, run the QE community of practice, and set the hiring bar.
- Choose what to automate: Review test design and code, and build shared frameworks where the team needs them.
- Shape how we test AI: Define how we test AI-powered and agentic features, and coach the team on AI tools.
- Show the results: Run blameless postmortems and publish a scorecard of escape rates and trends for engineering leadership.
- Shape engineering strategy: Work with the VP of Engineering and Engineering Managers on quality culture and where engineering goes next.
What we’re looking for
- Quality team experience: 7+ years in quality engineering, SDET, or similar roles, including leading or guiding a QA team or function. Heads of QA and leaders of QA divisions often do well in this role.
- Hands-on technical work: You stay close to the work, from analysis to test design to automation. Experience with Playwright, Cypress, or similar, and one language used in modern SaaS (TypeScript, Python, or Go).
- Evidence-based approach: A record of analyzing a quality process, choosing the metrics that matter, and cutting escaped defects.
- Cross-team influence: Experience building adoption of quality practices across Engineering, Product, Design, and Customer Success.
- AI fluency: Regular use of tools such as Cursor, GitHub Copilot, or Claude, with a deliberate review step before relying on the output.
- Root cause methods: Experience with blameless postmortems and structured RCA, such as 5 Whys, Fishbone, or CAPA.
- Startup pace: Comfort in a fast-moving, growth-stage environment.
- Education: BS in Computer Science, Software Engineering, or equivalent experience.
Nice to have
- AI evals: Evals for LLM-based or agentic features (datasets, graders, LLM-as-judge, regression suites in CI), with tools such as LangSmith, Braintrust, or DeepEval.
- Observability and analytics: Sentry, Datadog, Pendo, or Amplitude used to guide test strategy.
- Domain: Real estate, fintech, or enterprise B2B SaaS.
- Transformation: Led a move from manual testing to automation.
- AI-native company: Experience at an AI-era startup.
- Specialty depth: Performance, security, or chaos engineering.
- Public work: Conference talks or open source contributions.
The Perks & Culture:
- Medical, dental, & vision insurance coverage
- Hybrid 3-days in office policy in San Francisco
- Flexible Spending Account
- Paid Parental Leave
- 401(k)
- Company-sponsored commuter benefits
- Flexible time off policy
- Catered lunches and snacks
- Monthly wellness reimbursement
- The estimated pay range for San Francisco candidates for this position is $ 180,000– $230,000 base.
- This position is also eligible for Dealpath’s equity plan. Your compensation will be based upon several factors including your experience, qualifications, education, location, and the skills assessed in Dealpath’s interview process.
- Your actual compensation will be confirmed in writing at the time of offer.
- Dealpath’s compensation ranges are determined by current market data, so compensation data posted on our job posts may change as new market data becomes available.
About Dealpath
Dealpath is the world’s largest and most trusted AI-powered operating system for real estate investing. To date, the platform has powered more than $10 trillion in transactions, partnering with hundreds of firms, including leading global institutions such as Blackstone, Nuveen, LaSalle, CBRE IM, MetLife, Newmark, New York Life, UBS, Manulife, DWS, and Principal.
By bringing together the only private exchange for institutional real estate listings, investment data, and intelligent execution workflows into a single platform, Dealpath enables firms to capture more opportunities, make faster decisions, execute efficiently, and deliver superior returns.
Our company is led by an experienced team and backed by a combination of top tier venture capital firms and strategic industry partners including: Blackstone, Nasdaq, 8VC, JLL Spark, WTI, GreenSoil Investments, LeFrak, Milstein, Bechtel, and Morgan Stanley Expansion Capital.
We value your voice! If you get excited about solving real business challenges and working closely with other smart folks in a winning culture — we’d love to meet you!
Interview Process Notice
Dealpath conducts interviews via video conference. To support our interviewers with accurate note-taking, we may use AI-assisted transcription tools during your interview sessions. By participating in the interview process, you acknowledge that interviews may be recorded or transcribed using these tools for note-taking purposes only. Transcripts are used solely for internal evaluation and are not shared outside of the hiring team.