Backend Engineer

About Fathom: Fathom (fathom.ai) is a high-growth AI technology company on a mission to eliminate the needless overhead of meetings. Our advanced AI assistant captures, summarizes, and organizes the key moments of video calls, allowing teams to stay fully present without sacrificing context or operational clarity. As the #1 most installed AI meeting assistant across the Zoom and HubSpot marketplaces, and holding a perfect 5/5 score on G2 with 4,500+ reviews, Fathom is breaking revenue and usage records weekly. We are a tightly knit company that builds magical digital experiences through the hard work of focused builders, operating under core cultural pillars: Care Deeply, Seek Leverage, Share Ownership, Sustain Urgency, and Be Tenacious.

Position Overview

We are seeking a highly analytical, systems-minded, and performance-driven Backend Engineer to improve the reliability, scalability, and efficiency of our mission-critical services under a permanent, full-time fully remote engagement framework. Operating as a core infrastructure generalist within our engineering division, you will step up to claim direct technical, optimization, and scaling accountability over a collection of stateless and stateful services processing hundreds of millions of async jobs weekly. Shifting completely away from plain frontend UI adjustments, basic template generation, or manual database data logging, you will run an active high-throughput distributed system, custom container orchestration, and real-time audio/video file compilation laboratory—partnering face-to-face with platform infrastructure engineers, application developers, and technical support units. This position requires an engineering generalist with deep production depth who constructs resilient, distributed systems fluidly natively using Backend code structures, evaluates application cost and memory allocation models cleanly to optimize operational efficiency, and drives technical architecture evolutions confidently to support massive multi-region scale.

Key Responsibilities

• Scalable Service Engineering: Contribute to the architecture and scaling of highly distributed stateful and stateless multi-region backend systems natively utilizing Backend methodologies.
• Runtime Performance Tuning: Audit, profile, and optimize application memory behaviors, focusing heavily on Go runtime configurations and internal garbage collection performance.
• Container Lifecycle Orchestration: Architect, develop, and productize dedicated Kubernetes (k8s) operators to systematically control service lifecycles and rollout stages.
• Storage Layer Caching: Design and deploy high-velocity cloud storage caching mechanisms and data retrieval paths to minimize latency across user-facing layers.
• Asynchronous Job Management: Benchmark, scale, and insulate distributed job processing queues configured to process hundreds of millions of background actions weekly.
• Multi-Stage Deployment Management: Oversee gradual multi-stage system rollouts and feature testing to guarantee absolute correctness and cost efficiency under spiky workloads.
• Asynchronous Collaboration: Champion high-fidelity technical writing and documentation across internal communication repositories (Slack, Notion, Loom) to foster an elite remote workflow.

Required Skills & Qualifications

• Proven professional history building, scaling, and stabilizing production-grade software engines in high-volume SaaS or PaaS environments.
• Masterful production-level proficiency developing with Go, including a crisp, practical understanding of runtime profiling, benchmarking, and internal garbage collection management natively using Backend protocols.
• Strong operational familiarity configuring containerized deployments and cluster automation environments via Kubernetes (k8s).
• Demonstrated experience architecting web applications or cloud workers utilizing relational/non-relational memory frameworks such as Redis or PostgreSQL.
• Excellent communication and breakdown skills, with a proven ability to translate complex low-level insights cleanly to non-technical stakeholders.
• Complete independence in structuring individual workloads, setting tactical priorities, and committing to execution targets once alignment is established.
• Location Context: Position features 100% remote parameters open to qualified distributed systems engineers globally.

Preferred Strategic Indicators (Nice to Have)

• Applied background handling large-scale asynchronous video streaming networks or parsing media pipelines using utilities like ffmpeg.
• Prior background navigating hybrid code runtimes, explicitly utilizing Cgo compilation layers.
• Familiarity with alternative stacks and historical architectures, including Ruby on Rails, Docker environments, and Google Cloud Platform (GCP/GKE) services.

What We Offer

• Vetted, High-Leverage AI Startup Salary Blueprint: An exceptionally competitive baseline annual salary of $180,000 to $240,000, paired with meaningful corporate equity ownership options.
• The spectacular professional canvas to shape the underlying architecture of the world premier AI-driven meeting productivity layer.
• Profound work-from-home remote parameters providing an autonomous virtual office space with minimal synchronous meeting overhead.
• A direct, transparent interview path (with zero live whiteboard coding assignments) designed to evaluate real past architectural learning and execution depth.
• Comprehensive health wellness infrastructures, technical growth allowances, and direct proximity to a multi-time technical founder.