Founding Engineer
A16z Β· Austin, TX
- Location
- Austin, TX
- Funding
- N/A
- Posted
- Jul 30, 2026
A16z is hiring a Founding Engineer based in Austin, TX. Every apply link on Engg.space goes straight to the company's own careers page - no recruiter middleman, no generic job-board form.
Apply directly at A16zRole details
We are hiring a Founding Engineer to build and scale the systems that power Maestro β in person, in Austin. This role sits at the intersection of engineering, product, and operations. You will work directly with the Founder and partner closely with Product and Ops to translate real-world operational friction into reliable, AI-enabled software. This is not a ticket-taking role. This is a builder role. You will be responsible for shipping the automation, tooling, and AI systems that increase team capacity and improve member experience β and driving them to launch and adoption. π― MISSION Maestro is building a high-touch, AI-enabled travel platform for high-net-worth members. We combine human expertise with automation and intelligent systems to deliver exceptional travel experiences β while building operational leverage that allows us to scale sustainably. As a Founding Engineer, your mission is to turn AI and engineering effort into reliable, scalable systems that actually get used and reduce human work. We are early, fast-moving, and intentional about who we hire. Every person we bring in meaningfully shapes the company. π THE MULTIPLIER EFFECT At Maestro, we don't hire to redistribute work; we hire to create exponential leverage. Every hire must bring a unique superpower β whether that's technical judgment, systems thinking, or the ability to solve ambiguous problems under pressure. As a founding engineer, your code is the leverage: the systems you build should let the team do dramatically more without growing headcount linearly. π WHAT YOU'LL DO - Ship, debug, and improve production code across the stack β backend, APIs, and AI systems - Integrate and operationalize AI workflows (LLMs, orchestration, APIs, automation) that are stable, understandable, and trusted internally - Translate ambiguous product and ops needs into working software - Prioritize based on measurable business impact, in partnership with product - Make pragmatic tradeoffs between speed, quality, and scalability - Instrument what you build and track performance in real usage - Reduce manual, human-heavy workflows through thoughtful automation - Collaborate closely with our offshore engineering team β sharing context, reviewing work, and unblocking one another to keep delivery moving across time zones You will help us move from "high-touch but manual" to "high-touch and scalable." We hire for outcomes, not activities. In your first 3β6 months, you will: - Ship core AI workflows and integrations that are stable and adopted internally - Measurably reduce manual, repetitive operational work through automation - Establish reliability in the systems the team depends on daily - Ship consistently, with fewer blockers and surprises - Create systems that scale as membership grows π± THE MAESTRO CORE (UNIVERSAL COMPETENCIES) Regardless of the role, every Maestro team member must embody: - High Agency: You find a way over, under, or through obstacles without waiting for permission. - Execution Velocity: You move work forward with momentum and intentionality. - Judgment: You make smart tradeoffs under uncertainty. - Human-Centered Conduct: You treat people like people, even under high pressure. - Ownership: You act like it's yoursβwithout being told. π§© ARE YOU A STAGE FIT? We are an early-stage, high-growth company. This means we value slope over pedigree. We need productive challengers who: - Have thrived in ambiguity and incomplete inputs before β not just tolerated it. - Start by doing, not delegating β there are no "pure managers" here. - Optimize for leverage before elegance, and ship "good enough" systems that are reliable and adopted. - Admit uncertainty and ask for help early to protect team velocity. - Take initiative without waiting for perfect clarity. - Care about building durable systems, not just shipping features. π QUALIFICATIONS REQUIRED EXPERIENCE - 4+ years building and shipping production software (full-stack or backend-leaning) - Strong technical judgment across backend, APIs, and modern web - Hands-on ability to ship, debug, and improve code independently - Comfort making speed / quality / scalability tradeoffs at an early stage - Demonstrated ownership of outcomes (not just shipping features) STRONGLY PREFERRED - Experience building or integrating AI-enabled products (LLMs, orchestration, AI agents, automation, ML systems) - Experience increasing operational leverage (reducing manual work, improving capacity) - Experience building internal tools, operational systems, or workflow automation - Experience working collaboratively with distributed or offshore engineering teams - Experience in high-touch service environments (marketplaces, travel, fintech, concierge, logistics, etc.) - Comfort with metrics, instrumentation, and reliability practices - AI-first workflow β you actively use AI to increase your own and the team's efficiency π’ WORK MODEL - In-person / hybrid role, based in Austin, TX (minimum 3 days/week in-office). - In-person collaboration is core to how we work and learn as a team. πΈ COMPENSATION & GROWTH - Competitive salary based on experience, plus meaningful founding-level equity. - Equity is structured to align long-term ownership with company growth. - Significant room to grow scope and technical leadership as the company scales. - Significant opportunity for impact and cross-functional exposure as the company grows. π WHY JOIN MAESTRO? - Founding-Level Ownership from Day One β This is not a feature-factory role. You'll own core systems and technical decisions from the start, and directly influence company direction as one of our earliest engineers. - Build at the Inflection Point β We have paying members, real revenue streams, and strong early signal β but we're still small enough for your work to materially shape the company. - AI Applied to Real Problems β We use AI as infrastructure β embedded into workflows that increase advisor capacity and improve high-stakes decision-making. This
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