{"id":61515,"url":"https://alion.io/job/sunset-ai-product-engineer","title":"AI Product Engineer","company":{"id":28307,"name":"Replay","domain":"replay.ai","url":"https://alion.io/company/replay","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"A","score":100,"open_postings":13,"ghost_share":0,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-17T05:46:00Z"}},"role":"Backend","role_family":"Backend","seniority":null,"employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["New York, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":168000,"max_usd":354000,"period":"year","method":"role_country_seniority_unknown","sample_n":8485},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Function Calling","optional":false},{"name":"LangChain","optional":false},{"name":"LangGraph","optional":false},{"name":"LLM","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"Node JS","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"React.js","optional":false},{"name":"Structured Outputs","optional":false},{"name":"Synthetic Data","optional":false},{"name":"Tool Use","optional":false},{"name":"TypeScript","optional":false},{"name":"JavaScript","optional":true}],"status":"live","first_seen_at":"2026-08-13T19:39:09Z","employer_posted_date":"2026-08-13","last_verified_at":"2026-10-17T21:49:06Z","board_verified":true,"closed_at":null,"days_open":65,"trust":{"level":"ok","repost_count":1,"flags":[],"days_open":64},"description":"About Replay\nAt its core, Replay was founded to help founders. We started by supporting startups through shutting down, but we have since expanded into unlocking a new revenue stream for all types of businesses.\nIn 2025, we had a unique insight: the data every company generates each day through collaboration, communication, and building is some of the most valuable training data in the world. Public and synthetic data can only get frontier models so far, so the next generation of model progress depends on real, proprietary data grounded in how actual businesses operate. We are a primary source of it, partnering directly with the frontier AI labs building what comes next.\nWhy Join Replay Now\nWe have scaled from $0 to a multi-eight-figure run rate in a matter of months\n\nWe have raised from top-tier investors, including Floodgate, Afore, Ludlow, and Hustle Fund\n\nWe are small enough that you will carry outsized responsibility and grow as quickly as the company does\n\nYou will partner with and build for some of the fastest and most important companies in the world\n\nYou will help build a massive, category-defining business from the ground floor\n\nThe Role\nThis is a production product-engineering role for someone who has shipped and operated LLM-backed software-not a prompt-engineering, research, or company-wide AI strategy position.\nAs our Senior AI Product Engineer, you will turn our early dissolution support agent into a trustworthy product that resolves well-bounded customer needs and establishes the right operating model for more complex workflows. You will move between customer experience, application code, retrieval, tool contracts, model behavior, evaluation, permissions, observability, rollout, and production learning. The goal is correct resolution and customer trust-not maximum deflection or autonomy.\nWhat You'll Do\nOwn AI-assisted dissolution support from the customer problem through production behavior, measurement, and iteration\n\nDesign retrieval, context, structured outputs, tool contracts, orchestration, and deterministic boundaries for grounded, inspectable behavior\n\nBuild clear answer, status, no-action, and human-handoff experiences that remain useful when evidence or authority is incomplete\n\nCreate representative, versioned evaluations for routing, grounding, usefulness, safety, stability, and real customer outcomes\n\nShip with explicit permissions, tenant boundaries, privacy controls, auditability, canaries, rollback, and recovery\n\nInstrument runtime and tool reliability, latency, cost, repeat contact, support effort, and serious failure modes\n\nTurn production failures into durable product, evaluation, and system improvements\n\nDetermine whether complex workflows should be automated, AI-assisted, structured for a human, or deliberately remain human-owned, then build the approved product approach\n\nSimplify, replace, or remove agentic components when deterministic software or a clearer product experience would work better\n\nWork closely with Product, Support, Security, domain experts, and full-stack engineers who own the surrounding Dissolution product\n\nWhat Success Looks Like\nCustomers get correct, useful resolution for a meaningful set of dissolution needs-not merely fewer human replies\n\nUnsupported claims and unsafe actions remain inside explicit launch guardrails, with sensitive failures treated as stop-ship issues\n\nHuman handoffs are timely, accurate, and carry enough context to help the customer rather than restart the conversation\n\nNew intents move from evidence design through safe release using repeatable evaluation, tool, observability, and rollout infrastructure\n\nQuality, runtime reliability, latency, cost, privacy, and customer effort remain visible as the product grows\n\nAt least one valuable multi-step workflow has an evidence-backed operating model-automated, AI-assisted, or deliberately human-owned-with clear authority, auditability, and recovery\n\nYou Might Thrive Here If\nYou have personally owned a production software product, including an LLM-backed capability beyond a prototype\n\nYou are a strong product engineer who can build across customer experience, application code, backend systems, AI behavior, and production operations\n\nYou understand retrieval, context selection, structured outputs, tool use, orchestration, evaluation, and observability-and know when simpler, deterministic software is the better tool\n\nYou can turn ambiguous user needs into explicit evidence, state, authority, and failure boundaries\n\nYou have designed for unsupported claims, uncertainty, permissions, privacy, human escalation, rollback, and recovery\n\nYou use representative evidence to make ship, revise, or stop decisions rather than optimizing demos or one aggregate score\n\nYou enjoy learning a consequential domain and working directly with Product, Support, Security, and engineering partners\n\nYou use modern AI development tools fluently and verify their output with the same rigor you apply to product behavior\n\nThis Role May Not Be for You If\nYou want to focus primarily on model research, prompt iteration, or AI infrastructure without owning the complete customer and production outcome\n\nYou believe more autonomy, more model calls, or a more sophisticated agent framework is inherently better\n\nYou prefer to hand off evaluation, security, observability, or production operation after a prototype works\n\nYou want a company-wide AI charter rather than focused ownership of the Dissolution product\n\nBonus\nExperience building customer-support, operations, or multi-step workflow agents\n\nExperience with LangGraph, LangChain, or comparable orchestration approaches\n\nExperience with typed tool protocols, retrieval systems, golden datasets, offline evaluation, shadow deployments, or model-based judges\n\nExperience with privacy-sensitive, multi-tenant, audited, legal, financial, or other high-trust products\n\nStrong Python plus TypeScript, React, Node.js, or comparable full-stack experience","description_format":"text","description_chars":5979,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":[],"lifecycle":[{"event":"open","at":"2026-08-13T19:39:09Z"},{"event":"reopen","at":"2026-10-12T17:15:17Z"}],"visa":[],"liveness":{"score":9,"band":"cold","label":"Long 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