{"id":3711440,"url":"https://alion.io/job/toppan-merrill-data-engineer-ai-backend","title":"Data Engineer, AI Backend","company":{"id":2408462,"name":"Toppan Merrill","domain":"toppanmerrill.com","url":"https://alion.io/company/toppanmerrill","size_band":"501-1000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"A","score":93,"open_postings":14,"ghost_share":0,"stale_share":0.5,"repost_share":0,"time_to_fill_p50_days":18,"computed_at":"2026-11-05T05:54:30Z"}},"role":"Backend","role_family":"Backend","seniority":"senior","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Anaheim, United States","Saint Paul, United States","Denver, United States","Palo Alto, United States","New York, United States","United States"],"countries":["US"],"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":"Azure","optional":false},{"name":"Databricks","optional":false},{"name":"FastAPI","optional":false},{"name":"Python","optional":false},{"name":"Spark","optional":false},{"name":"Azure AKS","optional":true},{"name":"Datadog","optional":true},{"name":"Hybrid Search","optional":true},{"name":"Kubernetes","optional":true},{"name":"LangChain","optional":true},{"name":"LangGraph","optional":true},{"name":"OpenAI","optional":true},{"name":"RAG","optional":true}],"status":"closed","first_seen_at":"2026-11-03T23:23:52Z","employer_posted_date":"2026-11-03","last_verified_at":"2026-11-04T19:10:26Z","board_verified":false,"closed_at":"2026-11-04T19:10:26Z","days_open":0,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":0},"description":"Job Description:\nData Engineer, AI Backend\nShape the Future of AI in Capital Markets and Legal Disclosure\nAt Toppan Merrill, we’re building Quinn, a cloud-based platform that helps law firms, investment banks, and public companies draft, review, and file SEC documents, including IPO registration statements, prospectuses, proxy statements, and annual and quarterly reports.\nWe’re applying AI to one of the most consequential document workflows in the world, where precision, trust, and accountability matter most. You’ll join a small, highly visible team, work directly with senior engineering leadership, and help create AI capabilities used in complex legal and financial disclosure workflows.\nIn this role, you’ll build the data and service foundation behind Quinn’s in-editor AI: the API the editor team builds against, the pipelines and indexes over SEC filings that power peer-company analysis, and a citation layer that traces every AI answer back to the exact sentence it came from. You’ll own both the contract other teams depend on and the systems behind it, in a domain where an untraceable answer isn’t acceptable.\nWhat You Will Do\nPublish and own the AI backend’s API specification, starting with a working stub, then build and operate the production services behind it, keeping the contract stable and communicating changes clearly to the teams that depend on it.\nBuild a document-context service that gives the AI the relevant context from the document an attorney is working on, while respecting that attorney’s access permissions.\nBuild ingestion, processing, and indexing pipelines for SEC filings from EDGAR to support peer-company analysis.\nCreate a citation index that connects AI-generated answers to the exact source sentences in the underlying filings.\nBuild services that route requests across multiple AI models while providing logging, monitoring, reliability controls, and visibility into usage and cost.\nDevelop and maintain the pipelines that produce evaluation data used by data scientists to validate AI quality.\nEstablish data-quality, observability, and operational standards for the AI backend.\n Our stack: Python, FastAPI, Databricks (including Vector Search), Spark, LangChain/LangGraph, Azure OpenAI and Azure AI Foundry, Kubernetes (AKS), and Datadog.\nHow You’ll Work\nYou’ll own the AI backend’s data services and pipelines from initial design through production operation. You’ll work closely with the data scientists developing and evaluating the AI capabilities, the editor team building the customer-facing AI panel, and the platform engineers who own document access and authorization across Quinn.\nFirst 90 Days\nOwn the API specification and stub, and keep the contract stable as the editor team builds against it\nStand up the document-context service in a test environment\nGet SEC filing ingestion running for an initial set of companies\nRequired Qualifications\n5+ years of professional data engineering or backend engineering experience in Python.\nExperience building and operating production data pipelines at scale using Databricks, Apache Spark, or a comparable platform.\nExperience building and operating production Python services (FastAPI or similar), including APIs other engineering teams depend on: publishing, versioning, and maintaining a stable contract.\nExperience working with text or document data, search, indexing, or information-retrieval systems.\nStrong data modeling, pipeline reliability, testing, and observability practices.\nA track record of delivering against firm milestones with cross-team dependencies.\nPreferred Qualifications\nExperience with retrieval-augmented generation (RAG) or vector/hybrid search in production.\nExperience building citation, provenance, or source-traceability capabilities for search or AI-generated answers.\nExperience with SEC filings, EDGAR, XBRL, or other complex financial and regulatory documents.\nExperience with Azure data and AI services, including multi-model routing, usage monitoring, and cost controls.\nExperience building evaluation datasets or pipelines for generative AI.\nLearn more at Toppan Merrill Careers About Toppan Merrill.\nCompensation and Benefits\nWe understand that your skills deserve recognition. That’s why we offer a competitive pay scale ranging from $ 130K-$165K annually, based on experience and expertise. We believe in compensating our dedicated team members fairly for their hard work and commitment. Please note that actual salaries may vary within, above, or below this range based on factors such as education, training, experience, professional achievement, business needs, and location.\nToppan Merrill strives to provide our employees and loved ones with competitive benefits including:\nEnhanced Medical, Dental, Vision, and Life insurance for employees and dependents\nEmployer Contribution to 401(k)\nPaid time off including vacation, sick, community involvement, bereavement, jury duty, and holidays\nPaid parental leave \nPaid community involvement/volunteer days \nWellness Resources and Employee Assistance Programming \nToppan Merrill is an equal opportunity/affirmative action employer. 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