{"id":678933,"url":"https://alion.io/job/friendli-software-engineer-senior-backend-2","title":"Software Engineer – Senior Backend","company":{"id":673295,"name":"FriendliAI","domain":"friendli.ai","url":"https://alion.io/company/friendli","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"C","score":68,"open_postings":17,"ghost_share":0.529,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-30T05:48:23Z"}},"role":"Backend","role_family":"Backend","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Seoul, South Korea"],"countries":["KR"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"CI/CD","optional":false},{"name":"ClickHouse","optional":false},{"name":"FastAPI","optional":false},{"name":"GraphQL","optional":false},{"name":"gRPC","optional":false},{"name":"LLM","optional":false},{"name":"Multimodal AI","optional":false},{"name":"OpenTelemetry","optional":false},{"name":"PostgreSQL","optional":false},{"name":"Python","optional":false},{"name":"Rest API","optional":false},{"name":"SQL","optional":false},{"name":"Hugging Face","optional":true},{"name":"JavaScript","optional":true},{"name":"Kubernetes","optional":true},{"name":"Next.js","optional":true},{"name":"React.js","optional":true}],"status":"live","first_seen_at":"2026-03-15T13:31:27Z","employer_posted_date":"2026-03-15","last_verified_at":"2026-10-30T06:09:19Z","board_verified":true,"closed_at":null,"days_open":228,"trust":{"level":"ghost","repost_count":0,"flags":["stale","company_stale"],"days_open":227},"description":"About the Job\nWe believe using large language and multimodal models should be as simple as calling an API. To achieve this in production, we need to serve enterprises across clouds, with authentication, billing, multi-tenant isolation, and zero tolerance for downtime.\nWe are looking for a Senior Backend Engineer who is excited by the full breadth of what it takes to run a platform in production. You will own the business logic layer that sits between our inference engine and every customer who relies on it. Your work spans API engineering, service development, and data architecture. If you like solving problems that only reveal themselves in the wild, this is your role: edge cases in multi-cloud orchestration, enterprise requirements that don’t fit neatly into a spec, performance bottlenecks that are hard to reproduce.\nYou will move across domains, make decisions under uncertainty, and build systems that work cleanly, reliably, and at scale. We are looking for people with a track record of owning complex systems in production and solving unique problems. A great candidate is a strong collaborator who enjoys solving complex architectural challenges, cares deeply about developer workflows, and is eager to help define the future of AI adoption.\nKey Responsibilities\nOwn the architecture and evolution of core backend microservices powering our AI inference platform, from the API layer through business logic to the data layer.\n\nDesign and build production-grade APIs (REST, gRPC, GraphQL) that serve as the foundation for AI deployments, developer integrations, and enterprise workflows.\n\nBuild and scale enterprise-grade platform capabilities: authentication, RBAC, billing, organization management, and secure multi-tenant SaaS infrastructure.\n\nDevelop AI-specific platform features, including LLM deployment workflows and inference-specific service integrations.\n\nDesign and optimize data models and pipelines across OLTP (PostgreSQL) and OLAP (ClickHouse) systems.\n\nCollaborate with infrastructure engineers on multi-cloud deployment and resource orchestration pipelines.\n\nSet reliability and performance standards for the services you own, resolving production issues with urgency and rigor\n\nDrive engineering quality through design reviews, automated testing, and CI/CD.\n\nQualifications\n5+ years of backend or systems engineering experience in production environments\n\nBachelor's or Master's degree in Computer Science, Computer Engineering, or equivalent.\n\nExpertise in Python and modern frameworks (e.g., FastAPI); should be able to write code others learn from.\n\nStrong experience designing and operating distributed systems at scale.\n\nSolid API design experience across REST, gRPC, and GraphQL.\n\nProficiency in data modeling and SQL, with hands-on experience in PostgreSQL and OLAP systems such as ClickHouse.\n\nWorking knowledge of LLM serving.\n\nExperience building secure, multi-tenant SaaS architectures: authentication, RBAC, and compliance requirements.\n\nFamiliarity with cloud-native development and observability tooling (OpenTelemetry or equivalent).\n\nStrong systems thinking and ability to reason about failure modes.\n\nPreferred Experience\nHands-on experience with AI or model serving infrastructure.\n\nExperience with Kubernetes for production container orchestration and scaling.\n\nBackground building developer-facing SDKs, CLIs, or internal engineering platforms.\n\nExposure to multi-cloud environments and cross-cloud resource management.\n\nExperience leading incident response and postmortems for production systems.\n\nBasic familiarity with modern frontend frameworks (e.g., React/Next.js) for cross-functional collaboration.\n\nBenefits\nFlexible working hours\n\nDaily lunch and dinner provided; unlimited snacks and beverages\n\nSupportive and highly collaborative work environment\n\nHealth check-up support and top-tier equipment/hardware support\n\nA front-row seat to the generative AI infrastructure revolution\n\nCompetitive compensation, startup equity, health insurance, and other benefits.\n\nAbout FriendliAI\nFriendliAI is building the world’s best AI inference platform that makes large language and multi-modal models fast, efficient, and deployable at scale. We power high-throughput, low-latency AI workloads for organizations worldwide and integrate directly with Hugging Face, giving developers instant access to over 600,000 open-source models.\nWe are a small, fast-moving team doing work that matters at one of the most exciting moments in the history of technology. 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