AI​/ML Software Engineer Senior; TS​/SCI Poly

GCI embodies excellence, integrity and professionalism. The employees supporting our customers deliver unique, high-value mission solutions while effectively leveraging the technological expertise of our valued workforce to meet critical mission requirements in the areas of Data Analytics and Software Development, Engineering, Targeting and Analysis, Operations, Training, and Cyber Operations. We maximize opportunities for success by building and maintaining trusted and reliable partnerships with our customers and industry.

At GCI, we solve the hard problems. As an AI/ML Software Engineer, a typical day will include the following duties:

The AI/ML Software Engineer will design, develop, deploy, and maintain advanced artificial intelligence and machine learning solutions in mission-critical environments. The ideal candidate is a hands‑on engineer with experience building scalable AI‑powered applications and machine learning pipelines using cloud‑native services. This role requires expertise in integrating, deploying, and optimizing machine learning models, large language models (LLMs), retrieval‑augmented generation (RAG) systems, and data processing frameworks within secure cloud environments.

The successful candidate will possess strong software engineering fundamentals combined with practical experience in AI/ML development, MLOps, cloud infrastructure, and data engineering. They must be comfortable working within an Agile, cross‑functional team and demonstrate a passion for innovation, continuous learning, and operational excellence.

• Design, develop, test, debug, and deploy AI‑enabled software applications, machine learning services, and intelligent automation tools.
• Develop and maintain scalable cloud‑native and on‑prem AI/ML solutions supporting mission‑critical operations.
• Build and integrate machine learning models, generative AI capabilities, and LLM‑powered applications into production systems.
• Design and implement Retrieval‑Augmented Generation (RAG) architectures leveraging vector databases, embeddings, and enterprise knowledge repositories.
• Develop and maintain data ingestion, transformation, feature engineering, and model inference pipelines.
• Collaborate with data scientists, machine learning engineers, analysts, project managers, and subject matter experts to operationalize AI capabilities.
• Deploy AI/ML workloads within AWS‑based cloud environments using Infrastructure as Code (IaC) and automated CI/CD pipelines.
• Design and optimize vector search, semantic search, and traditional search solutions using Open Search, Elasticsearch, or equivalent technologies.
• Implement model monitoring, observability, performance tuning, and automated retraining workflows.
• Ensure responsible AI practices, including model explainability, governance, security, privacy, and compliance requirements.
• Troubleshoot complex production issues involving AI models, data pipelines, cloud services, and distributed systems.
• Maintain technical documentation for AI architectures, model deployment processes, and operational procedures.
• Research and evaluate emerging AI, machine learning, and cloud technologies and provide recommendations for continuous improvement.
• Partner with engineering teams to advance organizational AI capabilities and accelerate adoption of modern AI technologies.

• Bachelor's degree in Computer Science, Information Technology, or other related technical discipline, or equivalent combination of education, technical certifications, training, and work/military experience.

• Demonstrated hands‑on experience with Python and modern software engineering practices, including Git, automated testing, and code reviews.
• Demonstrated hands‑on experience developing and deploying RESTful APIs and microservices.
• Demonstrated experience building, integrating, and deploying machine learning models in production environments.
• Demonstrated experience with generative AI frameworks such as Lang Chain, Llama Index, Semantic Kernel, or equivalent technologies.
• Demonstrated experience working with Large Language Models (LLMs), prompt engineering, model…