Vice President of Engineering

About Us: Fluent Health is a dynamic healthcare startup revolutionizing how you manage your healthcare and that of your family. The company will provide customers with high-quality, personalized options, credible information through trustworthy content, and absolute privacy. To assist us in our growth journey, we are seeking a highly motivated and experienced Vice President of Engineering to play a pivotal role in future success. Website Link- https://fluentinhealth.com/ Job Description: We are looking for a Vice President of Engineering to own how software gets built at Fluent. While the Vice President of Engineering will partner on architecture, the heart of this role is systems, people, and execution. Today, engineering output is constrained by gaps in development practices, testing, AI quality systems, and team ownership. The Vice President of Engineering will be accountable for building a high-functioning engineering organization that can ship reliably, improve continuously, and earn user trust. You will be responsible for Establishing a modern, scalable SDLC, Raising product quality and reliability, Designing how developers, product, and QA work together, Building a culture of ownership, velocity, and continuous improvement, Implementing systems to make AI outputs consistent, testable, and trustworthy This role will combine hands-on leadership with system-building. Your primary role is to enable the team to deliver high quality production systems, and you probably have high curiosity that leads you to prototype internal tools or workflows. Responsibilities: 1. Own the Software Development Lifecycle (SDLC): Design and implement a clear, end-to-end development process Shift from end-of-cycle manual QA → continuous, automated testing Establish standards for: Code quality Testing coverage Release processes Incident response and debugging Ensure new code does not break existing functionality 2. Build a Scalable Testing & Quality System: Operationalize automated testing (unit, integration, E2E) Define testing expectations for engineers (tests written alongside code) Reduce reliance on manual QA as the primary quality gate Create visibility into quality (e.g., error rates, regression rates) 3. Establish AI Evaluation & Reliability Systems: Build evaluation (“evals”) frameworks to measure AI output quality Ensure consistent, deterministic-enough outputs for critical workflows Design human-in-the-loop systems where needed (e.g., review layers before data persistence) Prevent low-trust outputs from reaching users or databases Own quality across the AI → product → user pipeline Ensure engineering deliverables against compliance milestones 4. Drive Engineering Culture & Role Design: Redesign how Dev, Product, and QA collaborate Create a culture where: Engineers solve problems, not just implement tickets Testing is part of engineering, not a downstream function Iteration is expected and safe Remove friction that prevents engineers from acting with ownership 5. Develop the Engineering Team: Coach and level up engineers and engineering managers Set expectations for performance, ownership, and craft Improve estimation quality and delivery predictability over time Build a team that can scale with the company 6. Improve Velocity Without Sacrificing Trust: Balance speed and quality through better systems (not heroics) Replace fragile “scaffolding” over time with durable systems Introduce iterative shipping practices (vs. big-bang releases) 7. Clarify Accountability & Execution: Partner with CTO/CPO to refactor and set up delivery teams Create clear ownership of delivery across teams Establish realistic timelines and continuously improve forecasting Be the accountable leader for engineering execution Qualifications: Total Engineering experience of 12-15 years, with leadership experience of 5-7 Years. Having experience in early age startup of 3 years. Has led engineering organizations through 0→1 or 1→n scaling challenges Direct recent experience in a high growth startup Has implemented modern SDLC practices (CI/CD, automated testing, etc.) Has managed teams where quality is developer-owned Experience building AI-enabled dev teams Comfortable operating in ambiguity while creating structure Experience building AI-enabled products Has shifted teams from manual QA → developer-owned quality Has walked into early dev teams and improved them quickly Has seen great understands how strong engineering organizations operate at scale High urgency and energy; biased toward action Ownership mindset: accountable for outcomes, not just process Pragmatic: knows when to move fast vs. when to stabilize Willing to challenge existing norms and redesign how teams work Strong judgment under pressure Able to lead while comfortable going hands-on to boost (e.g., prototyping internal tools)