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:
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)
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