AI Engineer Security Clearance

Position: AI Engineer with Security Clearance
We are seeking an experienced AI / Generative-AI Engineer to build, deploy, and maintain scalable cloud-native AI applications and services. The ideal candidate will combine strong full-stack engineering skills with expertise in modern AI/ML methods, including large language models (LLMs), prompt engineering, and AI-driven automation.
• Key Responsibilities
* Design and develop end-to-end AI applications and services: from model integration to backend APIs and production deployment.
* Build and maintain ML/GenAI pipelines and infrastructure (data ingestion, preprocessing, model inference, result handling).
* Integrate AI/ML components (LLMs, embeddings, retrieval, RAG, vector stores) into scalable, secure cloud-based systems.
* Collaborate with cross-functional teams - product, data-science, Dev Ops - to gather requirements, implement AI-driven features, and deliver robust solutions.
* Write, test, and deploy production-grade code (backend and, optionally, frontend) that leverages AI capabilities.
* Maintain CI/CD pipelines, containerization, orchestration (e.g., with Docker, Kubernetes), and cloud infrastructure.
* Ensure security, data privacy, and compliance when handling sensitive data in AI workflows.
* Monitor and optimize performance, scalability, and reliability of AI services in production.
* Document system design, AI workflows, and best practices; mentor/guide junior engineers.
• Qualifications
* B.S. or higher in Computer Science, Software Engineering, or related technical field (or equivalent experience).
* 3+ years of professional software engineering experience building production-grade applications.
* Strong proficiency in Python; experience with AI/ML libraries/frameworks (e.g., PyTorch, Tensor Flow, or similar).
* Demonstrated experience with Generative AI / Large Language Models (LLMs), including prompt engineering, embeddings, retrieval-augmented generation (RAG), or related workflows.
* Familiarity with cloud platforms (AWS, Azure, GCP) and cloud-native deployment practices.
* Experience with containerization (Docker), orchestration (Kubernetes), and infrastructure-as-code / Dev Ops workflows.
* Ability to design scalable backend services, APIs, and integrate with other systems/data stores.
* Strong problem-solving, communication skills, and ability to work collaboratively across teams.