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AI/ML Engineer

Location: Remote Work Authorization: Must be able to work without sponsorship Clearance Requirement: Must be able to obtain and maintain a Federal or DoD Public Trust

Position Overview

We are seeking an experienced AI/ML Engineer to design, develop, and deploy production-ready artificial intelligence and machine learning solutions supporting mission-critical investigative and operational challenges.

This position will focus on Retrieval-Augmented Generation, conversational AI, agentic workflows, traditional machine learning, natural language processing, graph analytics, and entity resolution. The ideal candidate combines strong Python software engineering skills with hands-on experience building scalable AI/ML applications using large, complex structured and unstructured datasets.

Responsibilities

• Design, develop, and deploy end-to-end AI/ML applications, including Retrieval-Augmented Generation systems, AI chatbots, and agentic workflows.
• Build scalable data pipelines that process, transform, link, and prepare structured and unstructured data for AI models and applications.
• Develop machine learning models for classification, clustering, anomaly detection, risk scoring, predictive analytics, and pattern recognition.
• Apply graph analytics, network analysis, and link-analysis techniques to identify relationships among individuals, organizations, transactions, locations, and events.
• Develop entity-resolution capabilities to match, deduplicate, and link records across large, disparate datasets.
• Apply natural language processing techniques to extract entities, relationships, topics, events, and risk indicators from documents, case notes, and other unstructured data.
• Build and maintain REST APIs that serve model inferences and integrate AI capabilities into enterprise applications.
• Rapidly prototype and refine solutions supporting fraud detection, trafficking detection, investigations, data triage, search, optimization, and automated discovery.
• Collaborate with software engineers, data scientists, analysts, product teams, and mission stakeholders to translate operational needs into practical technical solutions.
• Contribute to application and platform architecture to ensure solutions are secure, scalable, reliable, and maintainable.
• Deploy AI/ML applications and models in AWS using cloud engineering, infrastructure-as-code, CI/CD, and DevOps best practices.
• Support explainable, auditable, and human-in-the-loop AI workflows that enable analyst review and investigative decision-making.

Required Qualifications

• Bachelor’s degree in computer science, engineering, data science, mathematics, or a related field.
• At least six years of relevant hands-on experience with Python and JavaScript and/or TypeScript.
• A master’s degree or relevant industry certification may substitute for up to two years of professional experience.
• Advanced Python experience supporting AI/ML application development, data engineering, data analysis, and model implementation.
• Experience developing production Retrieval-Augmented Generation applications, including retrieval optimization and re-ranking strategies.
• Experience building AI chatbots, conversational agents, or agentic AI applications.
• Hands-on experience with LangChain, Haystack, crewAI, LlamaIndex, or a comparable AI application framework.
• Experience developing and applying machine learning models for classification, clustering, anomaly detection, risk scoring, predictive analytics, or pattern recognition.
• Experience with graph analytics, network analysis, link analysis, or relationship discovery across complex datasets.
• Experience with entity resolution, record linkage, identity matching, deduplication, or similar data-matching techniques.
• Experience applying NLP techniques such as named entity recognition, semantic search, text classification, information extraction, topic modeling, or relationship extraction.
• Strong knowledge of Python data science and machine learning libraries such as NumPy, Pandas, Scikit-learn, NLTK, and OpenCV.
• Familiarity with deep learning frameworks such as PyTorch or TensorFlow.
• Experience with Elasticsearch, OpenSearch, or a comparable search technology.
• Experience working with PostgreSQL, Oracle, or similar relational databases.
• Experience with analytical or in-memory databases such as DuckDB.
• Strong SQL and data-modeling skills.
• Experience developing and integrating REST APIs.
• Experience with AWS services and SDKs, including Boto3.
• Ability to work with large, disparate datasets and identify hidden patterns, relationships, anomalies, and risk indicators.
• Strong analytical, problem-solving, collaboration, and communication skills.
• U.S. citizenship and the ability to obtain and maintain a Federal or DoD Public Trust.

Preferred Qualifications

• Experience with agentic AI frameworks such as AWS Strands Agents, PydanticAI, or similar technologies.
• Advanced prompt-engineering experience for complex reasoning, extraction, orchestration, and decision-support use cases.
• Experience developing asynchronous Python applications.
• Experience with Model Context Protocol servers, tool calling, and multi-agent workflows.
• Knowledge of GPU-accelerated computing, CUDA, or model-performance optimization.
• Experience with Neo4j, Amazon Neptune, TigerGraph, NetworkX, GraphFrames, or similar graph technologies.
• Experience supporting fraud detection, trafficking detection, investigations, intelligence analysis, case management, or law-enforcement-adjacent programs.
• Experience developing explainable AI/ML models that support analyst review, auditability, and investigative workflows.
• Experience deploying AI/ML solutions into secure federal cloud environments.
• Familiarity with geospatial analytics, temporal analytics, behavioral pattern detection, or advanced link analysis.
• Experience designing human-in-the-loop systems supporting case prioritization and operational decision-making.