Founding Engineer (AI | Robotics)

Sierra Studio

2d•Remote

About The Position

We are a mission-driven technology startup transforming the way in-home care is delivered through innovative AI solutions. Our platform unifies signals from cameras, sensors, wearables, and connected devices to turn raw data into secure, real-time insights and closed-loop care actions; giving families peace of mind, seniors dignified independence, and providers the tools to deliver safer, more proactive care. We're a small, mission-driven team tackling one of the most important challenges of our time: helping people age safely and independently at home. If that excites you, we'd love to have you join us. We're hiring our first in-house engineer. We want someone who can open the codebase, test ideas themselves, and get us real answers fast. Someone we can hand an open question to and get back working evidence, not an opinion. Most of your week will be spent writing code: prototypes, integrations, internal tools, and R&D experiments. The rest goes to being the technical reference inside the company, the person our engineering partner syncs with and the person our CEO turns to when something needs a real answer. A big part of the job is technical validation. We're constantly running into questions like: can we run this on-device? Is this open source speaker stack good enough? What would it take for a humanoid robot to do something actually useful in a home? You build the answer, bring back your findings, and we decide together what makes it into the product. Turning a question into working evidence in days instead of quarters is the single biggest thing this hire unlocks. The role is remote from Brazil. You should be willing to travel to the US a couple of times a year to work hands-on with the team and the hardware, especially as our robotics work ramps up. As the team grows, this role is expected to evolve into technical leadership, with the opportunity to hire and lead other engineers. We're looking for someone who is a strong senior individual contributor now and wants that next step.

Requirements

5+ years building software professionally, with a track record of shipping things real people used.
Strong hands-on engineering skills. You write code every day and you're good at it: comfortable across the stack, deep somewhere.
Practical AI/ML fluency. You've built with LLMs, speech, or perception systems and understand where they break, not just how to call the API.
Experience taking a product from zero to a working first version, in an environment with incomplete information and no dedicated team.
Excellent written and verbal communication. You'll be the connective tissue between technical execution and business stakeholders who don't share your context by default.
Autonomy and ownership. No one is going to hand you a groomed backlog; you decide what matters this week and you're right about it most of the time.
Willing and able to travel to the US a couple of times a year.

Nice To Haves

Experience with robotics, humanoids, embodied AI, or IoT and connected devices.
Comfort with hardware-adjacent work: edge deployment, audio pipelines, sensors, on-device inference.
Experience working alongside distributed engineering teams.
Early-stage startup background. You've been the person who did it all before there was a team.
Product instinct: you have opinions about what should be built, not only how.
Background in a technical discipline (CS, engineering) or equivalent self-taught technical depth.

Responsibilities

Write production and prototype code across the stack.
Stand up MVPs and working demos fast, then validate them with real data or real users before we commit engineering budget to them.
Build the internal tools and lightweight automation that let a small team punch above its weight.
Ship integrations with the devices, sensors, and third-party services Grace depends on.
Take open technical questions (new models, new hardware, new open source components) and turn them into working evidence.
Run experiments end to end: scope them, build them, measure the results, write up what you found, and recommend a call.
Experiment with robotics hands-on. We expect four to five humanoids on site, and someone needs to be in the room with them.
Evaluate build vs. buy vs. integrate decisions, and be able to defend the answer.
Answer day-to-day technical questions from the CEO and the business side directly and plainly, without a translation layer.
Give leadership honest reads on feasibility, effort, and risk, so roadmap conversations are grounded in reality.
Push back on scope creep and unrealistic timelines when a project's ambitions outpace its resourcing, and say so early.
Support in building technical narratives for decks and funding rounds.