Senior AI/ML Engineer (IC)

Location: Sterling, VA or Aurora, CO

This is a hybrid position; however, it is required that successful candidate and report on-site on a regular basis and as-needed .

Clearance: Active Top Secret clearance REQUIRED.

Position Overview

Crown Point Technologies is seeking a Senior AI/ML & Generative AI Solutions Engineer to support the development and deployment of advanced artificial intelligence capabilities for a U.S. Intelligence Community customer.

This position will focus on integrating AI/ML, generative AI, Large Language Models, retrieval technologies, and agentic capabilities into a broader mission software platform.

The engineer will work with software engineers, knowledge graph engineers, data engineers, DevOps personnel, cybersecurity teams, commercial software vendors, and government stakeholders to prototype, develop, evaluate, and operationalize AI-enabled capabilities within a classified environment.

The work supports a mission-focused, space-based software capability and provides an opportunity to apply modern AI technologies to complex mission, engineering, and operational data.

Candidates are not expected to have experience with every AI technology listed below. We are looking for engineers who understand modern AI application architectures and are comfortable combining software engineering with AI/ML technologies.

Responsibilities

• Design, develop, prototype, and integrate AI/ML capabilities supporting mission requirements.
• Develop applications using Large Language Models and generative AI technologies.
• Design and implement Retrieval-Augmented Generation architectures.
• Develop semantic search, retrieval, ranking, and information discovery capabilities.
• Build AI agents and agentic workflows capable of interacting with enterprise data, applications, and services.
• Develop Graph-RAG or knowledge-graph-enabled AI solutions.
• Integrate LLMs with APIs, databases, knowledge graphs, vector stores, and enterprise applications.
• Develop embedding pipelines and vector-based retrieval capabilities.
• Evaluate models, prompts, retrieval strategies, and AI system performance.
• Develop AI-enabled data extraction, classification, summarization, reasoning, and analytical capabilities.
• Develop software services and APIs supporting AI-enabled applications.
• Configure and extend commercial AI/ML platforms.
• Support deployment of AI capabilities within classified or disconnected computing environments.
• Work with infrastructure and DevOps teams to containerize and operationalize AI workloads.
• Support model monitoring, application logging, troubleshooting, and performance optimization.
• Evaluate emerging AI technologies and rapidly prototype capabilities in response to mission requirements.
• Collaborate with customer personnel, software vendors, data engineers, knowledge engineers, architects, and other technical stakeholders.

Desired Technical Skills

Strong candidates will have experience in several of the following areas:

Generative AI & LLM Applications

• Large Language Models
• Generative AI
• Retrieval-Augmented Generation
• Graph-RAG
• Prompt engineering
• AI agents and agentic workflows
• Tool/function calling
• LLM application frameworks
• Model evaluation and testing

Search & Retrieval

• Embeddings
• Vector databases
• Vector search
• Semantic search
• Information retrieval
• Hybrid search
• Reranking
• Knowledge-graph-enabled retrieval

AI/ML Engineering

• Python
• Machine learning pipelines
• Natural language processing
• Model integration
• Data preparation
• Model evaluation
• Applied machine learning
• PyTorch, TensorFlow, Hugging Face, or similar technologies

Experience with Siemens AI Studio or similar enterprise AI development platforms is highly desirable.

Software Engineering

• Python, Java, JavaScript/TypeScript, or similar languages
• REST APIs
• Microservices
• Backend application development
• Enterprise application integration
• Git and modern software development practices

Knowledge & Data Technologies

Experience with any of the following is a plus:

• Knowledge graphs
• RDF/OWL
• SPARQL
• Graph databases
• Ontologies
• Structured and unstructured data integration
• Data pipelines

DevOps & Deployment

• Docker
• Kubernetes
• Linux
• CI/CD
• DevSecOps
• GPU-enabled computing environments
• Application monitoring and logging
• Deployment within classified or disconnected environments

Qualifications

• Active Top Secret U.S. Government security clearance required.
• Bachelor’s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Software Engineering, Computer Engineering, or a related technical discipline, or equivalent professional experience.
• Professional experience in AI/ML engineering, software engineering, data science, applied AI, or a related technical field.
• Experience building production-oriented AI applications rather than exclusively performing theoretical or academic research is highly desirable.
• Strong software development and troubleshooting skills.
• Ability to rapidly evaluate and learn emerging AI technologies.
• Ability to work across AI, software, data, infrastructure, and security disciplines.
• Strong written and verbal communication skills.
• Ability to communicate AI concepts, limitations, tradeoffs, and technical approaches to engineers, architects, program leadership, vendors, and government customers.