Need: Lead AI Engineer Job ID: 26-00830
Steave Nickson
Please find the specs of the requirement below; kindly send suitable profiles to srik...@dwintechcorp.com
Job Details:
Job ID: 26-00830
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
CLIENT: FINRA
PAYRATE: 60/hr on C2C DOE
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, GCP, 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
---------------------------Thanks & Regards