Lead AI Engineer

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.

 JN -06

#LI-JS1

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, Google Cloud Platform, 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.

Education Requirements

• Bachelor''s or Master''s degree in Computer Science, AI/ML, or related field.
• PhD preferred but not required.
  
  Thanks,
  Rohit