Hybrid 3 days onsite / 2 days remote in Rockville, MD
Our client seeks a Lead AI Engineer to design and deliver an AI-powered compliance screening platform for regulated communications across text and multimedia. The role will architect multimodal ingestion, retrieval-augmented generation, and LLM-driven reasoning with robust explainability and auditability. The engineer will set technical strategy, establish evaluation and risk controls, and mentor a team while collaborating with compliance, legal, and product stakeholders. The work will advance reliable compliance intelligence for financial use cases.
We can facilitate w2 and corp-to-corp consultants. For our w2 consultants, we offer a great benefits package that includes Medical, Dental, and Vision benefits, 401k with company matching, and life insurance.
Rate: $99.00 to $110.00/hr. w2
JN -052026-106906
Responsibilities
Design and implement end-to-end AI pipelines for document ingestion across PDFs, HTML, images, audio, and video.
Build multimodal extraction using OCR, layout parsing, and vision-language models.
Develop LLM-driven compliance reasoning and scalable RAG grounded in regulatory content.
Translate regulatory frameworks into machine-interpretable logic.
Create rule classifiers, risk scoring models, and violation detection workflows.
Evaluate LLMs for action-specific tasks and implement prompt engineering and tool usage.
Apply fine-tuning strategies, guardrails, and hallucination mitigation techniques.
Integrate multimodal models for charts, images, and disclosures.
Deliver explainable, regulator-ready outputs with evidence-backed decisions and linked text spans.
Ensure full audit trails for all AI decisions and outputs.
Define and track precision, recall, and false-negative metrics with human-in-the-loop reviews.
Conduct adversarial and edge-case testing to improve reliability.
Establish best practices for architecture, coding standards, and MLOps.
Collaborate with compliance, legal, and product teams.
Mentor engineers on AI and ML best practices.
Experience Requirements
8+ years in software engineering or machine learning with production AI/ML delivery.
Experience in regulated industries such as finance, legal, or healthcare.
Strong expertise in NLP and large language models.
Hands-on experience with retrieval-augmented generation.
Proficiency in model evaluation and benchmarking, including LLM-specific evaluation.
Familiarity with multimodal AI across text, image, and layout.
Proficiency in Python and LLM orchestration or agent frameworks such as LangChain or AWS Strands.
Experience with vector databases such as PG Vector or Pinecone.
Background in document processing pipelines, including OCR and PDF parsing.
Experience with cloud platforms such as AWS, GCP, or Azure.
MLOps, CI/CD, model monitoring, and scalable distributed system design.
Experience with explainable AI and understanding of auditability and governance requirements.
Exposure to industry regulations and compliance frameworks (preferred).
Experience building legal or compliance-focused AI systems (preferred).
Familiarity with marketing or advertising review processes (preferred).
Experience analyzing structured and unstructured documents, including charts and disclosures (preferred).
Background in hybrid AI systems combining rules and machine learning (preferred).
Education Requirements
Bachelor's or Master's degree in Computer Science, AI/ML, or related field.
PhD preferred but not required.