Head of Applied AI

Niural • New York City, NY

2d • Onsite

About The Position

Niural is the AI-native platform that unifies payroll, compliance, HR, and financial operations across 150+ countries. Our AI agent layer, EMMA, doesn’t sit on top of the product, it is the product. We process high-stakes, multi-jurisdictional payroll and compliance data where a single error can mean regulatory penalties, missed paychecks, or broken trust. We’re hiring a Head of Applied AI to own the entire AI engineering function. This is a hands-on technical leadership role for someone who ships production systems, not someone who manages from a distance. You will design, build, and iterate on the AI systems that make Niural’s platform intelligent, and you will set the engineering standard for the team that grows around you. Backed by Marathon, M13, and Inspired Capital.

Most “Head of AI” roles at startups mean wrangling a chatbot wrapper or running prompt experiments. This one is different because the underlying domain is genuinely hard and unsolved: Multi-jurisdictional document understanding across 150+ countries, each with distinct payroll rules, tax codes, and employment regulations, in dozens of languages. Structured data extraction from payroll and compliance inputs where accuracy isn’t aspirational, it’s a regulatory requirement. You will build systems where the cost of a hallucination is a compliance violation, not a bad search result. Agentic workflows (EMMA) that need to execute autonomously on financial transactions while remaining explainable and auditable. This isn’t a chatbot that just answers questions, it’s autonomous payroll execution. Real-time anomaly detection on financial data across currencies, jurisdictions, and tax regimes simultaneously. If you want to do serious applied AI work in a domain where the output actually matters, where model performance translates directly to whether people get paid correctly, this is the role.

Requirements

• 6+ years hands-on in ML or AI engineering, with at least 2 years building and shipping production LLM systems, not notebooks, not prototypes, production.
• Strong Python engineering skills. You write production-quality code that other engineers can review, test, and extend.
• Direct experience with RAG architectures, prompt engineering, fine-tuning, and LLM evaluation, including building eval datasets and tracking model performance over time.
• Solid command of ML infrastructure: model serving, vector databases, embedding pipelines, and monitoring in production environments.
• Experience working with structured and unstructured data in a high-accuracy, low-tolerance-for-error context.
• Demonstrated ability to translate ambiguous business requirements into concrete technical approaches and ship them cross-functionally.
• Comfortable with a high degree of ownership in an early-stage environment where the right process needs to be created, not followed.

Nice To Haves

• Experience with agentic systems and multi-agent orchestration in production- LangGraph, AutoGen, CrewAI or similar (not just toy examples).
• Background in NLP applied to legal, financial, or regulatory document processing, especially multilingual.
• Familiarity with global payroll, employment law, or multi-jurisdictional compliance data.
• Prior experience as an early AI hire at a Series A - C company where you built the function from scratch.

Responsibilities

• Design, build, and ship LLM-powered features end-to-end: document understanding, structured data extraction from payroll and compliance inputs, multi-step reasoning workflows, and intelligent automation across the Niural platform.
• Construct rigorous evaluation frameworks with ground-truth datasets, regression tracking, and clear production-readiness criteria.
• Build and own the core AI stack: RAG pipelines, vector stores, embedding systems, fine-tuning workflows, model serving, and observability tooling.
• Implement hallucination controls, confidence scoring, human-in-the-loop review flows, and audit trails for model-driven decisions.
• Work with product and engineering to translate business requirements into concrete model specifications, data requirements, and acceptance criteria.
• Set the engineering foundations, code standards, review processes, documentation practices, that will support a growing AI team.

Benefits

• Competitive base + significant equity at a high-growth, venture-backed company approaching Series B.
• Onsite at Niural’s New York headquarters, working directly with a focused, technical team.
• Direct access to the CEO and CTO.
• Your technical decisions will have immediate, visible product impact.
• Well-resourced AI infrastructure budget and access to frontier model APIs from day one.
• A domain with genuine complexity, real data, and problems that have not been solved yet, across 150+ countries.
• Comprehensive health, dental, and vision coverage.
• Learning and development budget.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed