Job description

STAFF BACKEND ENGINEER — DISTRIBUTED SYSTEMS, PLATFORM ABOUT US BUILDING THE RANKING INTELLIGENCE LAYER FOR THE INTERNET. Sequen provides an integrated platform that pairs cutting-edge frontier ranking models with the infrastructure to run them in production—at sub-25ms latency and enterprise scale. The world's largest retailers, marketplaces, and travel platforms use Sequen to rank, recommend, and personalize, with an autonomous research engine that compounds model performance into revenue and margin lift measured in hundreds of millions of dollars per customer. ABOUT THE ROLE - Build the platform: Build and scale robust, concurrent core platform components designed to handle Sequen's rapid growth and high transactional throughput. - Architect composable systems: Design and architect composable platform components that deliver exceptional value across a wide variety of enterprise use cases. - Collaborate across teams: Partner closely with product and ML engineering teams to deeply understand their requirements and build platform capabilities that accelerate feature delivery. - Drive architectural decisions: Make critical build-versus-buy decisions, evaluating and implementing third-party or open-source solutions when they yield the highest strategic impact. - Set technical vision: Define the long-term technical direction, standards, and vision for various product and platform features. - Partner with research: Collaborate closely with our ML research scientists to quickly prototype and launch new capabilities based on research breakthroughs. ABOUT YOU - Proven track record: Bring 8+ years of practical experience as a backend or platform engineer building highly performant, scalable distributed systems. - Go language mastery: Possess an expert-level command of Go (Golang) as your primary programming language for building highly concurrent systems. - Service-oriented expertise: Demonstrate strong systems-level skills and extensive experience designing and operating complex service-oriented architectures. - Startup DNA: Thrive in early-stage, fast-moving, or rapidly evolving environments, with a proven history of building and scaling systems from 0 to 1. - Extreme ownership: Take absolute accountability for your work, navigating ambiguity with agility and proactively resolving obstacles to deliver results. - System-wide comfort: Operate comfortably across any layer of the stack, diving into cloud infrastructure, core microservices, or developer tooling to deliver complete, effective solutions. - Passion for AI systems: Enjoy working alongside a fast-paced, elite team tackling cutting-edge challenges at the intersection of systems engineering and AI ranking. - Product-focused mindset: Approach platform engineering with a product-focused lens, caring deeply about building systems that are robust, highly scalable, and easy to use. - Academic foundations: Hold a Bachelor’s degree in Computer Science, Software Engineering, or equivalent professional experience. STRONG CANDIDATES MAY ALSO BRING - Polyglot capabilities: Bring a firm grasp of Python for machine learning pipelines and scripting integrations. - Infrastructure fluency: Know your way around container orchestration (kubectl, Kubernetes) and Infrastructure-as-Code (terraform). - ML alignment: Have worked directly with NLP and ML models, understanding their deployment patterns, performance capabilities, and operational limits. - Modern API design: Possess deep experience designing and implementing highly performant, secure RESTful and gRPC APIs. - Full-stack exposure: Bring lightweight experience with React and modern frontend frameworks to help build internal diagnostics and visualization tools. WHAT WE OFFER - High-impact influence: A high-autonomy, staff-level Individual Contributor (IC) role directly shaping our core backend architecture and platform evolution. - Pioneering systems: The unique opportunity to build mission-critical, low-latency systems powering advanced ML experiences at enterprise scale. - Top-tier reward: Highly competitive base salary, plus meaningful early-stage equity. - Premium benefits: Full health insurance coverage, unlimited paid time off, and a highly collaborative, world-class engineering culture.

Requirements

Must-haves

STAFF BACKEND ENGINEER — DISTRIBUTED SYSTEMS, PLATFORM
Build the platform: Build and scale robust, concurrent core platform components designed to handle Sequen's rapid growth and high transactional throughput.
Architect composable systems: Design and architect composable platform components that deliver exceptional value across a wide variety of enterprise use cases.
Collaborate across teams: Partner closely with product and ML engineering teams to deeply understand their requirements and build platform capabilities that accelerate feature delivery.
Drive architectural decisions: Make critical build-versus-buy decisions, evaluating and implementing third-party or open-source solutions when they yield the highest strategic impact.
Set technical vision: Define the long-term technical direction, standards, and vision for various product and platform features.
Partner with research: Collaborate closely with our ML research scientists to quickly prototype and launch new capabilities based on research breakthroughs.
Proven track record: Bring 8+ years of practical experience as a backend or platform engineer building highly performant, scalable distributed systems.
Go language mastery: Possess an expert-level command of Go (Golang) as your primary programming language for building highly concurrent systems.
Service-oriented expertise: Demonstrate strong systems-level skills and extensive experience designing and operating complex service-oriented architectures.
Startup DNA: Thrive in early-stage, fast-moving, or rapidly evolving environments, with a proven history of building and scaling systems from 0 to 1.
Extreme ownership: Take absolute accountability for your work, navigating ambiguity with agility and proactively resolving obstacles to deliver results.
System-wide comfort: Operate comfortably across any layer of the stack, diving into cloud infrastructure, core microservices, or developer tooling to deliver complete, effective solutions.
Passion for AI systems: Enjoy working alongside a fast-paced, elite team tackling cutting-edge challenges at the intersection of systems engineering and AI ranking.
Product-focused mindset: Approach platform engineering with a product-focused lens, caring deeply about building systems that are robust, highly scalable, and easy to use.
Academic foundations: Hold a Bachelor’s degree in Computer Science, Software Engineering, or equivalent professional experience.
Polyglot capabilities: Bring a firm grasp of Python for machine learning pipelines and scripting integrations.
Infrastructure fluency: Know your way around container orchestration (kubectl, Kubernetes) and Infrastructure-as-Code (terraform).
ML alignment: Have worked directly with NLP and ML models, understanding their deployment patterns, performance capabilities, and operational limits.
Modern API design: Possess deep experience designing and implementing highly performant, secure RESTful and gRPC APIs.
Full-stack exposure: Bring lightweight experience with React and modern frontend frameworks to help build internal diagnostics and visualization tools.

Nice-to-haves

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mlgogolangaipythonmachine learningkubernetesapireact

Platform: ashby
Effort: quick

Benefits

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Health Insurance

Vision

Paid Time Off