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Lead AI Engineer

Eliassen Group

Description:
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


#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, 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.
Vacancy posted 2 days ago
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