Staff Software Engineer (Backend) job opportunity at MLabs.



Date2026-02-18T09:51:05.914Z bot
MLabs Staff Software Engineer (Backend)
Experience: 6-years
Pattern: Remote
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loacation Remote, United States Of America
loacation Remote....United States Of America

Staff Software Engineer (Backend) Location:  San Francisco, New York, or Remote (US) On-site/Remote| Full-time Compensation: $225K – $300K  Our client is a high-growth, venture-backed organization (YC W24) that has raised over $35M to pioneer the next generation of autonomous digital workers. Unlike traditional chatbots or copilots, our client builds fully autonomous "AI employees" that research leads, manage complex outbound sequences, handle deliverability infrastructure, and self-optimize through behavioral patterns. Currently at $8M+ ARR and scaling rapidly, the organization is deep in the development of its next-generation platform—a step change in the capabilities of AI agents. The backend is the core of this transformation, processing millions of signals to facilitate autonomous decision-making. Our client is seeking a Staff Software Engineer to serve in a foundational role, owning major segments of the platform infrastructure and driving high-throughput AI orchestration. The engineering culture is flat, high-velocity, and results-oriented. There is no red tape; engineers are expected to own outcomes end-to-end, from architecture and design to deployment and monitoring. Key Responsibilities AI Orchestration: Design and build the high-throughput pipelines and services that allow autonomous agents to process massive volumes of data and make reliable, real-time decisions. Platform Infrastructure: Own significant portions of a unified product stack that replaces traditional sales tools, including email infrastructure, CRM integrations, lead databases, and campaign engines. End-to-End Ownership: Take full accountability for the lifecycle of features—designing, building, deploying, and monitoring services without a separation between architecture and implementation. Rapid Iteration: Ship code constantly in a continuous release environment, maintaining high velocity while ensuring system stability. Technical Leadership: Contribute to the technical roadmap, mentor peers, and maintain high standards for reliability, observability, and testing across a distributed system. Interview Process Recruiter Screen: An introductory chat to discuss background and alignment. Technical Interview I: A 60-minute technical session with a member of the engineering team. Technical Interview II: A second 60-minute session focused on deeper technical capabilities. Leadership Interview: A 30-minute conversation with the CPTO regarding system design and vision. Culture & Values Interview: A final 30-minute session with the CEO to ensure alignment with the organization’s core principles. Experience: 6+ years of backend engineering experience, preferably within a high-growth startup environment where systems were owned end-to-end. Technical Proficiency: Strong experience building and operating data-intensive services at scale. Expertise in TypeScript/Node is preferred, though proficiency in Python, Go, or similar languages is acceptable if fundamentals are strong. Systems Knowledge: Deep understanding of distributed systems, database performance, and API design. Cloud Infrastructure: Hands-on experience with cloud-native technologies, including containers, orchestration (Kubernetes/ECS), CI/CD, and monitoring. AI-Native Workflow: A "5x engineer" mindset with the ability to effectively leverage modern AI coding tools to accelerate development. Communication: Clear ability to explain complex technical systems to both engineering peers and product leadership. Tech Stack Familiarity: Experience with or a desire to work in an environment utilizing PostgreSQL, Redis, Kubernetes, Mastra, Temporal, Langfuse, and AWS .

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