Senior AI Engineer, Unstructured AI
$204,000–$255,000 year
HybridNew York, United States
Job Summary
Own end-to-end technical delivery of Unstructured AI systems, building full-stack services that ingest, process, and enrich large volumes of unstructured content from distributed enterprise silos. Define scope and acceptance criteria for complex systems under real ambiguity, writing and reviewing production-grade backend code in Python and FastAPI. Integrate data from diverse sources like SharePoint, Salesforce, and internal APIs to provide context for AI features, while partnering across engineering, product, and sales teams to ensure alignment from prototype to rollout. Occasional frontend development may be required. This hybrid role in New York requires at least two days in the office.
Required Qualifications
- Strong proficiency in Python (data processing, API development, and integrations)
- Hands-on work with LLM-based and AI-driven enrichment models (e.g., classification, entity extraction, deduplication, PII detection)
- Production experience with Spark or comparable big data frameworks
- Experience shipping tested, reviewed production services rather than notebooks
- A track record of starting things: a specific example where you took a vaguely-scoped problem, defined the MVP yourself, wrote down your assumptions, and shipped it — without a PM converting it into tickets first
- Solid understanding of data pipelines, microservice architecture, and API design
- Experience ingesting and processing data from third-party enterprise sources (e.g., SharePoint/OneDrive, Salesforce, and SaaS-based knowledge bases)
- Familiarity with metadata systems, data cataloging, or document AI workflows
- Knowledge of model evaluation best practices
- Experience with search relevance
- A bachelor's degree or equivalent related working experience is required
- Agentic engineering in practice, not just tool usage: you can say where an agent loop earns its keep, what guardrails and structured outputs keep it in bounds, and how you manage its context. Same discipline when coding agents write for you — tests, review gates, repo conventions
- Calm, structured decision-making under tight timelines or ambiguity
- Capable of communicating clearly across engineering, product, and field teams, ensuring alignment from prototype to rollout
- Experienced in spotting risks early and course-correcting without friction when delivery timelines are tight
- Someone who cares deeply about data quality, precision, and governance
- Strong communication and stakeholder-management skills across technical and business teams
- This is a hybrid role based in our New York office. Our hybrid model means you'll work from the office at least two days each week
- This position is not eligible for visa sponsorship
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