What are the responsibilities and job description for the Lead AI Engineer - Compliance Screening Platform position at Jobs via Dice?
Software Guidance & Assistance, Inc., (SGA), is searching for a Lead AI Engineer - Compliance Screening Platform for a CONTRACT assignment with one of our premier Regulatory clients in Rockville, MD or Tysons, VA.
We are seeking a Lead AI Engineer to design and build an AI-powered compliance screening platform that evaluates communications for adherence to regulatory standards and industry guidelines.
This is a high-impact role at the intersection of artificial intelligence, regulatory compliance, and risk management. You will 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
SGA is an Equal Opportunity Employer and does not discriminate on the basis of Race, Color, Sex, Sexual Orientation, Gender Identity, Religion, National Origin, Disability, Veteran Status, Age, Marital Status, Pregnancy, Genetic Information, or Other Legally Protected Status. We are committed to providing access, equal opportunity, and reasonable accommodation for individuals with disabilities in employment, and our services, programs, and activities. Please visit our company to request an accommodation or assistance regarding our policy.
We are seeking a Lead AI Engineer to design and build an AI-powered compliance screening platform that evaluates communications for adherence to regulatory standards and industry guidelines.
This is a high-impact role at the intersection of artificial intelligence, regulatory compliance, and risk management. You will 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:
- Document ingestion (PDF, HTML, images, video/audio)
- Multimodal extraction (OCR, layout parsing, vision-language models)
- LLM-driven compliance reasoning
- Build scalable retrieval-augmented generation (RAG) systems grounded in regulatory content
- Translate regulatory frameworks into machine-interpretable logic
- Develop:
- Rule classifiers (e.g., performance claims, disclosures)
- Risk scoring models
- Violation detection workflows
- Evaluate LLMs that are specific for actions
- Implement:
- Prompt engineering and tool usage
- Fine-tuning strategies where appropriate
- Guardrails and hallucination mitigation techniques
- Integrate multimodal models for charts, images, and disclosures
- Build systems that generate:
- Clear, regulator-ready explanations
- 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)
- 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
- 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
- Bachelor's or Master's degree in Computer Science, AI/ML, or related field
- 8 years of experience in software engineering or machine learning
- Proven track record of building and deploying production AI/ML systems
- AI / Machine Learning
- Strong expertise in:
- NLP and large language models (LLMs)
- Retrieval-augmented generation (RAG)
- Model evaluation and benchmarking
- Familiarity with multimodal AI (text image layout)
- 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)
- Cloud platforms (AWS, Google Cloud Platform, or Azure)
- MLOps, CI/CD pipelines, and model monitoring
- Scalable system design and distributed architectures
- Experience with explainable AI (XAI)
- Understanding of auditability and governance requirements
- Exposure to industry regulations and compliance frameworks is a strong plus
- PhD preferred but not required
- Experience in regulated industries (finance, legal, healthcare) strongly preferred
- 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)
SGA is an Equal Opportunity Employer and does not discriminate on the basis of Race, Color, Sex, Sexual Orientation, Gender Identity, Religion, National Origin, Disability, Veteran Status, Age, Marital Status, Pregnancy, Genetic Information, or Other Legally Protected Status. We are committed to providing access, equal opportunity, and reasonable accommodation for individuals with disabilities in employment, and our services, programs, and activities. Please visit our company to request an accommodation or assistance regarding our policy.