Lead Artificial Intelligence Engineer
HireTalent - Staffing & Recruiting Firm, Rockville, MD, United States
Location: Rockville, MD or Tysons, VA/Hybrid
Duration: 12 Months Contract
About the Role
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.
What You'll Do
Design and implement end-to-end pipelines for:
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:
LLM & Model Strategy
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
Explainability & Auditability
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
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
Strong expertise in:
NLP and large language models (LLMs)
Retrieval-augmented generation (RAG)
Model evaluation and benchmarking
Familiarity with multimodal AI (text + image + layout)
Tools & Frameworks
Experience with LLM orchestration or agent frameworks such as:
LangChain
AWS Strands
Document processing pipelines (OCR, PDF parsing tools)
Systems & Infrastructure
Cloud platforms (AWS, GCP, 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)
#J-18808-Ljbffr
Duration: 12 Months Contract
About the Role
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.
What You'll Do
Design and implement end-to-end pipelines for:
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:
LLM & Model Strategy
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
Explainability & Auditability
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
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
Strong expertise in:
NLP and large language models (LLMs)
Retrieval-augmented generation (RAG)
Model evaluation and benchmarking
Familiarity with multimodal AI (text + image + layout)
Tools & Frameworks
Experience with LLM orchestration or agent frameworks such as:
LangChain
AWS Strands
Document processing pipelines (OCR, PDF parsing tools)
Systems & Infrastructure
Cloud platforms (AWS, GCP, 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)
#J-18808-Ljbffr