HYBRID::Lead AI Engineer at Rockville, MD or McLean, VA

Hello,

Greetings.!

This is Hima from Appridat Solutions LLC. I was reviewing your resume online and would like to talk to you regarding an exciting opportunity for Lead AI Engineer at Rockville, MD or McLean, VA. We have with one of Appridat Solutions LLC premier clients.

Title: Lead AI Engineer

Location: Rockville, MD or McLean, VA (Hybrid 3 days onsite with 2 days remote)

Duration: 6 Months with possible extension

Interview process: Phone, Onsite panel

Job Summary:

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. The ideal candidate will lead the development of systems that analyze content across multiple formats, including PDFs, emails, social media, and video, and generate auditable, explainable compliance decisions.

Key Responsibilities

AI System Architecture

Design and implement end-to-end AI pipelines for document ingestion across PDFs, HTML, images, video, and audio

Build multimodal extraction workflows using OCR, layout parsing, and vision-language models

Develop LLM-driven compliance reasoning systems

Build scalable retrieval-augmented generation (RAG) systems grounded in regulatory content

Compliance Intelligence

Translate regulatory frameworks into machine-interpretable logic

Develop rule-based and AI-driven classifiers for areas such as performance claims and disclosures

Build risk scoring models and violation detection workflows

LLM and Model Strategy

Evaluate and select large language models appropriate for specific compliance use cases

Implement prompt engineering, tool use, and fine-tuning strategies where appropriate

Design guardrails and hallucination mitigation techniques

Integrate multimodal models to assess charts, images, and disclosures

Explainability and Auditability

Build systems that generate clear, regulator-ready explanations for decisions

Ensure outputs are evidence-backed, with text spans linked to applicable rules

Maintain full audit trails for all AI-generated decisions

Apply strong understanding of LLM evaluation frameworks, with DeepEval preferred

Evaluation and Risk Management

Define and track model performance metrics such as precision, recall, and false negatives

Implement human-in-the-loop review workflows

Conduct adversarial and edge-case testing

Continuously improve model quality, reliability, and safety

Technical Leadership

Establish best practices for architecture, coding, MLOps, and deployment

Partner cross-functionally with compliance, legal, and product teams

Mentor engineers and provide technical leadership on AI and machine learning best practices

Qualifications

Education

Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field

PhD preferred but not required

Experience

8 years of experience in software engineering, machine learning, or applied AI

Proven track record of building and deploying production-grade AI/ML systems

Experience in regulated industries such as finance, legal, or healthcare strongly preferred

Technical Skills

Strong expertise in natural language processing and large language models

Hands-on experience with retrieval-augmented generation (RAG)

Experience with model evaluation, benchmarking, and performance testing

Familiarity with multimodal AI, including text, image, and layout understanding

Tools and Frameworks

Strong Python development experience

Experience with LLM orchestration or agent frameworks such as LangChain or AWS Strands

Experience with vector databases such as PGVector or Pinecone

Familiarity with document processing pipelines, including OCR and PDF parsing tools

Systems and Infrastructure

Experience with cloud platforms such as AWS, Google Cloud Platform, or Azure

Knowledge of MLOps, CI/CD pipelines, model monitoring, and deployment best practices

Strong background in scalable system design and distributed architectures

Highly Desired

Experience with explainable AI and model transparency

Understanding of auditability, governance, and compliance requirements

Exposure to regulatory frameworks and compliance controls

Preferred Qualifications

Experience building legal, risk, or compliance-focused AI systems

Familiarity with marketing or advertising review workflows

Experience analyzing both structured and unstructured documents, including charts and disclosures

Background in hybrid AI systems that combine rules-based logic with machine learning

Regards,

Hima Bindu

Appridat solutions LLC.

5655 Peachtree Parkway, Suite 212, Peachtree Corners, GA 30092

PHONE:*533 | Fax

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