{"id":4320173,"url":"https://alion.io/job/clera-founding-forward-deployed-engineer-28","title":"Founding Forward Deployed 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":40,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":6,"computed_at":"2026-11-14T05:58:10Z"}},"role":"Solutions","role_family":"Solutions","seniority":"middle","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"posting_text","remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":["New York, United States"],"countries":["US"],"hiring_countries":["US"],"hiring_countries_total":1,"salary":{"min":180000,"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":"dbt","optional":false},{"name":"LLM Evaluation","optional":false},{"name":"Machine Learning","optional":false},{"name":"SQL","optional":false}],"status":"live","first_seen_at":"2026-11-14T17:05:59Z","employer_posted_date":"2026-11-14","last_verified_at":"2026-11-14T19:35:39Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"About the Role\nOwn customer deployments from initial data access through delivery of a trusted system with measurable business outcomes. This founding role sits at the intersection of data engineering, applied AI, and customer success, while also building reusable tools and frameworks to improve future deployments.\nWhat You'll Do\nPartner with revenue and operations leaders to understand business objectives and decide what is worth building.\n\nLead customer onboarding, scope data access, and map undocumented warehouse schemas to business concepts.\n\nInterview customer data and business teams to establish clear definitions and validate the resulting ontology.\n\nBuild customer-facing signals and workflows, including the agent setups behind them, and diagnose issues in their outputs.\n\nAgree on success measures and develop analysis that demonstrates delivered impact, including clear explanations when outcomes fall short.\n\nTurn deployment learnings into reusable validation frameworks, evaluation harnesses, and mapping tools.\n\nWhat We're Looking For\nAt least 3 years of experience in a technical, customer-facing role such as forward deployed engineering, solutions engineering, or software engineering with substantial customer exposure.\n\nStrong data warehouse skills, including SQL and dbt, and the ability to navigate undocumented schemas.\n\nApplied data science and machine learning experience, including statistical or modeling fundamentals and work with distributions, seasonality, validation, and calibration.\n\nExperience building custom agent configurations beyond default implementations and improving their outputs.\n\nAbility to resolve conflicting business definitions through customer interviews and data validation, and to define success metrics that support credible impact analysis.\n\nA degree in statistics, mathematics, computer science, or a comparable quantitative field; experience in early-stage startups or as a founder is valuable.\n\nCareful, evidence-driven judgment and comfort with ambiguity, hands-on work, and owning outcomes end to end.\n\nCompensation & Benefits\nBase salary: $180,000 to $250,000 annually. 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