{"id":2734490,"url":"https://alion.io/job/clera-senior-applied-ai-engineer-2","title":"Senior Applied AI Engineer","company":{"id":2706,"name":"Clera","domain":"getclera.com","url":"https://alion.io/company/clera","size_band":"11-50","is_staffing_agency":true,"employer_type":"agency","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"B","score":80,"open_postings":30,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":6,"computed_at":"2026-10-19T05:45:15Z"}},"role":"AI/ML","role_family":"AI/ML","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":["San Francisco, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":150000,"max":250000,"currency":"USD","period":"year","gross":null,"usd_annual":250000},"salary_estimate":null,"experience_years_min":3,"visa_sponsorship":true,"relocation_package":false,"has_equity":false,"technologies":[{"name":"LLM","optional":false},{"name":"LLM Evaluation","optional":false},{"name":"Python","optional":false}],"status":"live","first_seen_at":"2026-10-16T17:10:29Z","employer_posted_date":"2026-10-16","last_verified_at":"2026-10-19T18:54:46Z","board_verified":true,"closed_at":null,"days_open":3,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":3},"description":"About the Role\nOwn the agent infrastructure that helps AI systems execute tasks reliably, retain useful context over time, and involve people when needed. You will work across agent orchestration, memory, evaluation, and production reliability, shipping systems for real users and improving them through production feedback.\nWhat You'll Do\nBuild and maintain infrastructure that lets agents execute tasks reliably across many iterations.\n\nDesign memory and retrieval systems that preserve client context from messy operational data.\n\nDevelop evaluation harnesses that teams can use to make production deployment decisions.\n\nMeasure, test, troubleshoot, and improve agent systems, including failure recovery and reliability.\n\nCollaborate with customers and contribute to infrastructure, orchestration, and team growth as needed.\n\nWhat We're Looking For\nAt least 3 years building and shipping LLM agents that ran unattended in production for real users.\n\nExperience building evaluation harnesses used to guide production releases.\n\nStrong Python skills for production systems, plus hands-on experience with agent orchestration, infrastructure, or workflow management.\n\nExperience implementing memory and context retrieval for operational data, beyond demo datasets.\n\nExperience with agent tooling, frameworks, or libraries, and production patterns for retries, failure recovery, and reliability.\n\nA track record of taking a technical project from conception to production; open-source agent tooling or LLM infrastructure experience is a plus.\n\nCompensation & Benefits\nBase salary is $150,000 to $250,000 USD annually, plus meaningful early equity. 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