Lead AI Engineer

Lead AI Engineer – Compliance Screening Platform

Design and build an AI-powered compliance screening platform that evaluates communications for adherence to regulatory standards and industry guidelines. High-impact role at the intersection of artificial intelligence, regulatory compliance, and risk management.  Lead the development of systems that analyze content across formats (PDFs, emails, social media, video) and generate auditable, explainable compliance decisions.

Responsibilities:

AI System Architecture

Design and implement end-to-end pipelines for:

o   Document ingestion (PDF, HTML, images, video/audio)

o   Multimodal extraction (OCR, layout parsing, vision-language models)

o   LLM-driven compliance reasoning

Build scalable retrieval-augmented generation (RAG) systems grounded in regulatory content

Compliance Intelligence

Translate regulatory frameworks into machine-interpretable logic

Develop:

o   Rule classifiers (e.g., performance claims, disclosures)

o   Risk scoring models

o   Violation detection workflows

LLM & Model Strategy

Evaluate LLMs that are specific for actions

Implement:

o   Prompt engineering and tool usage

o   Fine-tuning strategies where appropriate

Guardrails and hallucination mitigation techniques

Integrate multimodal models for charts, images, and disclosures

Explainability & Auditability

Build systems that generate:

o   Clear, regulator-ready explanations

o   Evidence-backed decisions (text spans linked to rules)

Ensure full audit trails for all AI-driven outputs

Expert-level understanding of LLM evaluation frameworks (deepeval preferred)

Evaluation & Risk Management

Define and track key metrics (precision, recall, false negatives)

Implement human-in-the-loop review workflows

Conduct adversarial and edge-case testing

Continuously improve model performance and reliability

Technical Leadership

Establish best practices for architecture, coding, and MLOps

Collaborate cross-functionally with compliance, legal, and product teams

Mentor a team of engineers on best AI/ML practices

Qualifications:

Education

Bachelor''s or Master''s degree in Computer Science, AI/ML, or related field

PhD preferred but not required

Experience

8+ years of experience in software engineering or machine learning

Proven track record of building and deploying production AI/ML systems

Experience in regulated industries (finance, legal, healthcare) strongly preferred

Technical Skills

AI / Machine Learning

Strong expertise in:

o   NLP and large language models (LLMs)

o   Retrieval-augmented generation (RAG)

o   Model evaluation and benchmarking

·       Familiarity with multimodal AI (text + image + layout)

Tools & Frameworks

Python ecosystem

Experience with LLM orchestration or agent frameworks such as:

• LangChain, AWS Strands

Vector databases (e.g., PG Vector, Pinecone)

Document processing pipelines (OCR, PDF parsing tools)

Systems & Infrastructure

Cloud platforms (AWS, Google Cloud Platform, or Azure)

MLOps, CI/CD pipelines, and model monitoring

Scalable system design and distributed architectures

Compliance & Risk Awareness (Highly Desired)

Experience with explainable AI (XAI)

Understanding of auditability and governance requirements

Exposure to industry regulations and compliance frameworks is a strong plus

Preferred Qualifications

Experience building legal or compliance-focused AI systems

Familiarity with marketing/advertising review processes

Experience analyzing structured and unstructured documents (including charts and disclosures)

Background in hybrid AI systems (rules + machine learning)