MTS

About Attention Engineering We are an applied AI lab building truly personal intelligence. Our platform runs continuously in the background - monitoring, understanding, and acting on everything you do - to build the deepest context layer ever built on a consumer desktop. The gap between how the top 0.001% of people use AI today - elaborate Claude Code configs, massive context files, and engineered workflows - and how everyone else uses it is only growing. We think the company that bridges that gap and creates a consumer product that actually understands you will be one of the most important companies built in this decade. We are a small, talent dense team that comes from MIT, SMU, Harvard, and Cambridge – ex-CitSec and Optiver quants, ML researchers, and IOI gold medalists. We’re backed by $2.25M from Neo, Village Global, SV Angel, Joe Montana, and others. The Role We are hiring one title across multiple strengths. At a team this size, you will own large, critical parts of the system. We hire across a few different spikes, but the bar in every case is exceptional. You’re spike may be: AI Runtime & Agent Orchestration: context management, tool use, VLMs, model selection, output quality in production. Search, Retrieval, Vector Systems & Data Infrastructure: Embedding pipelines, ranking and retrieval architecture, and the data infrastructure underneath them. Evals, Applied ML & Model Quality: feedback loops that improve model behavior in production, regression detection, thinking rigorously about quality at scale and measuring what matters. Backend Systems & Workflow Architecture : automations, async pipelines, and service architecture. PostgreSQL, Redis, Pub/Sub, FastAPI Infrastructure, Cloud Platform & Reliability: high-concurrency, low-latency, distributed systems under real production load. GCP, Terraform, Docker, Cloud Run. Internal Tools, Operator Workflows & Debugging Surfaces: tooling that makes the rest of the team faster. Dashboards, observability, and debugging interfaces that leverage the team. Swift / macOS: SwiftUI-first with AppKit where bridging requires it What You’ll Do You will work directly alongside the founding team with no layers between you and the decisions that matter. No one owns all of this. But everyone touches most of it. Product & Platform Ship consumer-facing features directly – interfaces, agent behaviors, and workflows used by real people every day Prototype fast and iterate based on what users actually do, not what they say Built and integrate new platform capabilities – memory, context, real-time triggers, and proactive agent behaviors – into polished product experiences Design observability surfaces and internal tooling that give the team leverage Infrastructure & Systems Own and evolve our infrastructure stack as concurrent agent executions and data throughput scale Harden distributed systems for concurrency, fault tolerance, and low latency Build abstractions that simplify architecture and increase velocity across the team What a Strong Fit Looks Like You are unusually strong in at least one domain and don’t insist on staying there You’ve owned real systems in production You are comfortable with broad ownership at a small team where scope expands faster than title You move between product work, infrastructure, and debugging without losing rigor or momentum You have strong engineering judgement and communicate clearly about tradeoffs under pressure You are high and low ego. The talent bar is high here, but no important problem is beneath anyone Who You Are You are high-intensity and care deeply about what you build You have fun solving problems other think are impossible You are an owner – when something is broken, you fix it; when something is missing, you build it You are curious about the research frontier and want to work somewhere that takes it seriously You are collaborative and kind, but you don’t need external validation to move fast People who tend to fit A distributed systems engineer interested in consumer AI A backend engineer with strong product instincts who has outgrown their current scope An applied ML engineer who likes production software and doesn't want to be siloed A Swift engineer who has shipped a real macOS app A founding engineer at a previous company who owned more than their title suggested Why Attention Engineering You will be on the founding team at a company with an applied and research roadmap no one else is pursuing The problems we face are new and genuinely hard We’ve built a generational team to pursue these problems What matters If your background doesn’t fit cleanly into one of the buckets above, that’s fine. Here we insist on no labels. We care about ownership, technical depth, and slope, not just your past CV. Tell us what you are unusually good at, what systems you’ve truly owned, what broke under your watch and how you fixed it, and why it transfers here. Include a link to your GitHub, a project you’re proud of, or a breakdown of the hardest technical problem you’ve solved. Compensation, Benefits, & Relocation Total Compensation: $150k base + significant early-stage equity Housing with housekeeping and laundry service (~$65k value) Breakfast, Lunch, and Dinner covered Full relocation support Full health, vision, and dental coverage Visa sponsorship available