{"id":415016,"url":"https://alion.io/job/evolver-agency-enterprise-platform-architect","title":"Enterprise Platform Architect","company":{"id":155158,"name":"Evolver","domain":"evolver.agency","url":"https://alion.io/company/evolver","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","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":"2026-10-24T06:02:35Z"}},"role":"DevOps","role_family":"DevOps","seniority":"staff","employment_type":null,"work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Palo Alto, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":155000,"max_usd":302000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":564},"experience_years_min":10,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Azure","optional":false},{"name":"LLM","optional":false}],"status":"live","first_seen_at":"2026-08-25T18:21:20Z","employer_posted_date":"2026-09-09","last_verified_at":"2026-10-24T22:56:24Z","board_verified":true,"closed_at":null,"days_open":60,"trust":{"level":"ok","repost_count":0,"flags":["company_stale"],"days_open":59},"description":"About Us \nWe are transforming core enterprise functions by combining frontier AI, strong engineering, and deep domain expertise. Our platform is used by a growing number of Fortune 1000 companies to execute complex, high-value work. \nWe are building enterprise AI for environments where accuracy, reliability, security, scalability, and economics matter. \nRole Overview \nWe are looking for an experienced Enterprise Platform Architect to further push the availability, reliably, scalability, performance, and cost efficiency of our platform. \nYou will work across Engineering, Cloud Infrastructure, DevOps, QA, and AI teams to establish measurable requirements, identify architectural platform bottlenecks and opportunities, and define enhancements. \nResponsibilities \nAvailability & Resilience \nDefine measurable availability, resilience, and recovery requirements. \nArchitect for failures across infrastructure, APIs, databases, external dependencies, and AI models. \nDesign redundancy, failover, retries, timeouts, graceful degradation, and recovery mechanisms. \nIdentify and eliminate critical single points of failure. \nEstablish resilience, failover, and recovery testing with clear production-readiness metrics. \nIdentify gaps, drive remediation, and validate readiness for enterprise production. \nScalability & Performance \nDefine measurable targets for throughput, concurrency, latency, document size, storage growth, and model capacity. \nArchitect the platform to scale predictably across customers, workloads, and data volumes. \nLead capacity planning across compute, storage, databases, networking, and AI infrastructure. \nEstablish load, stress, endurance, and performance-testing standards. \nIdentify and eliminate architectural and performance bottlenecks. \nMaintain performance benchmarks and ensure the platform meets enterprise-scale requirements before production. \nCost Efficiency \nDefine and track platform unit economics, including cost per transaction, workflow, and AI execution. \nEstablish cost targets and identify the primary drivers of platform economics. \nOptimize model selection, routing, caching, batching, and reuse. \nMove workloads from expensive LLM reasoning to code, ML, smaller models, or deterministic systems where appropriate. \nImprove infrastructure utilization and eliminate unnecessary computation. \nEnsure the platform remains economically viable as workload volume and complexity scale. \nQualifications \nExperience: 10+ years of experience architecting and building enterprise SaaS platforms or similarly complex production systems. \nEducation: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field. \nTechnical Skills: \nDeep expertise in distributed systems, reliability, scalability, performance, and cloud architecture. \nStrong experience with Azure or other hyperscale cloud platforms. \nStrong understanding of databases, APIs, networking, storage, containers, and distributed compute. \nFamiliarity with AI/LLM infrastructure, model APIs, inference architectures, and AI economics. \nExperience with 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