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Reflexive Concepts is seeking a skilled Software Engineer III! The Software Engineer shall be responsible for the design, development, and deployment of a Retrieval Augmented Generation (RAG) solution deployed in a HPC Linux environment. Candidates applying for this position must be familiar with LLMs (Large Language Models), LLM orchestration frameworks, knowledge retrieval, and security-aware AI systems. Qualifications: Active TS/SCI + FS Polygraph Master's degree in Computer Science or related discipline from an accredited college or university, plus five (5) years of experience as a SWE, in programs and contracts of similar scope, type, and complexity OR Bachelor's degree in Computer Science or related discipline from an accredited college or university, plus seven (7) years of experience as a SWE, in programs and contracts of similar scope, type, and complexity OR Nine (9) years of experience as a SWE, in programs and contracts of similar scope, type, and complexity. Required Skills + Experience : Experience with Linux system administration, CLI, and shell scripting Experience with containerization technologies such as Docker, PodMan, and containerd Experience deploying containerized services under Kubernetes or Docker Compose orchestration Recent software development experience using Python, Golang Familiarwith RAG pipelines, LLMs, and embedding models Experience with CI/CD principles, methodologies, and tools including GitLab CI Experience using metrics and monitoring tools such as Prometheus and Grafana Experience using Git Source Control System Desired Skills + Experience: Experience working with and debugging GPU-enabled applications Familiar with LLM orchestration such as Open API API Experience with distributed processing technologies such as Spark, Dask, or Ray for data processing ETL workflows Experience with SQL, Elasticsearch, and Vector databases Experience with HTMX or Hyper-script Experience with HW/SW aspects of multi-node, multi-GPU AI model training Knowledge of AI inferencing solutions such as Nvidia NIM/TRITON, vLLM, and direct deployment (e.g. Ray) Experience with the Atlassian suite of tools including Confluence and Jira #J-18808-Ljbffr