AI Engineer

Position: Lead AI Engineer
Location: Rockville, MD / Tysons, VA #HYBRID
Duration: 12 months #Contract
Interview: 1st Video and 2nd IN-Person

Job Description:

Lead AI Engineer Compliance Screening Platform
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
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

Compliance Intelligence:

-Translate regulatory frameworks into machine-interpretable logic

-Develop:

• Rule classifiers (e.g., performance claims, disclosures)
• Risk scoring models
• Violation detection workflows

LLM and 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 and 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)

Evaluation and Risk Management:

-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:

-Bachelor's or Master's degree in Computer Science, AI/ML, or related field

-PhD preferred but not required

-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:

-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)

Tools and Frameworks:

-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)

Systems and Infrastructure:

-Cloud platforms (AWS, GCP, or Azure)

-MLOps, CI/CD pipelines, and model monitoring

-Scalable system design and distributed architectures

Compliance and 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)

Thanks and Regards,

--

LAXMAN

KMM Technologies, Inc.

CMMI Level 2 | ISO 9001 | ISO 20000 | ISO 27000 Certified

Tel:

Python, LLM, RAG, MLops